• Lack of legal basis for martial law: Yoon’s justification — political crisis and opposition party tyranny — did not meet the constitutional or legal criteria.

• Procedural violations: Yoon bypassed required Cabinet deliberation, failed to properly announce martial law details, and did not notify the National Assembly.

• Obstruction of the National Assembly: The president used the police and military to block and remove lawmakers, infringing their constitutional rights and immunities.

• Suppression of political opponents: Yoon ordered intelligence officials to track opposition leaders for possible arrests.

• Misuse of the military for political purposes: Military forces were deployed to interfere with democratic institutions.

• Undermining democracy and the separation of powers: The martial law orders barred political and legislative activity nationwide.

• Violations of civil liberties: Citizens’ political rights, freedoms of assembly and occupation were unjustly restricted.

• Illegal raid on the National Election Commission: Yoon ordered a warrantless military operation against the NEC, breaching its independence.

• Threats to judicial independence: He tracked former justices, creating a chilling effect on the judiciary.

Following the ruling, Yoon was immediately removed from office, thus mandating a new presidential election within 60 days.

Far from resolving the polarizing debate over Yoon’s martial law declaration of December 3-4, the unanimous ruling may have exacerbated it. The dominant progressive Democratic Party (DP) saw the ruling as affirming its view of Yoon and his conservative People’s Power Party supporters as legacies of the nation’s authoritarian past. International media, such as the BBC, reinforced this narrative by interviewing reasonable, younger, English-speaking progressive activists and politicians, and translating the angry Korean outbursts of older, conservative protestors.

Conversely, conservatives saw the ruling as affirming progressive dominance of the nation’s major institutions and marginalizing conservative voices; specifically, conservative lawyers argued, the ruling relied on contradictory and unreliable testimonies that the President ordered the arrest of political leaders or attempted to obstruct the National Assembly, despite Yoon’s claim to the contrary. Others made less-substantiated claims about Chinese and North Korean influence.

What we have then is a mainstream media narrative on the impeachment ruling that selectively highlights certain forms of information that support the progressive party, along with an alternative media narrative that makes both reasonable and poorly founded claims. All of this illustrates a general pattern of what we may term asymmetric polarization in South Korea and other countries, where two sides act in ways that threaten liberal democratic norms and individual rights through different methods, depending on their levels of representation within elite institutions.

In a 2022 Pew Research survey, South Koreans ranked the most polarized among 19 countries, with 49% of respondents endorsing the idea of “very strong conflicts between people who support different political parties.” The US was ranked second, with 41% claiming the same.

Vigorous disagreement among supporters of different ideologies and parties is not necessarily problematic for liberal democracy. What is problematic is when partisans view and treat their opponents as illiberal, harmful actors, who do not deserve the protection of liberal procedural rights and norms (PRN), which include both formal-legal rights such as free speech, due process, and equal treatment under the law, and non-legal norms such as journalistic impartiality and academic objectivity, which are associated with fair procedures in a liberal democracy.

When competing groups of partisans exercise differential power in mainstream bureaucratic institutions, they may violate liberal PRN in different ways. To the extent that supporters of one party or ideology dominate institutionally, and view members of the opposing party as illiberal, they can exercise institutional power to marginalize opposing viewpoints and information. Conversely, to the extent that members of the opposing party view mainstream institutions as biased and oppressive, they reject them and turn to alternative outlets. Non-mainstream media offer both substantive information suppressed in elite institutions, and unsubstantiated information and conspiracy theories that fuel grassroots support for radical disruption.

In America’s post-1960 culture war politics, partisan identity is significantly defined by one’s view of the nation’s political and religious founding, as heroic and inspiring or oppressive. Progressive-leaning Democrats often view the nation’s white, male, Christian-dominated past as problematic and champion its challengers, while conservatives take the opposite position.

In the past two decades, self-identified progressives in the US have gained unprecedented dominance in colleges and universities. From 1989 to 2016-2017, the ratio of progressive to conservative faculty more than doubled from 2.3:1 to 5:1, with 60% identifying as liberal and only 12% as conservative; among campus administrators, the ratio was 12:1, as only 6% identified as conservative. In the latest 2021-22 survey, the ratio of liberal to conservative faculty skewed further to 7:1.

Progressive faculty and administrators often frame conservative viewpoints as illiberal and harmful, and exercise their institutional power to marginalize them. Sixty-three percent of liberal faculty believe it can be acceptable to shout down speakers, compared to 47% of moderates and only 12% of conservatives. Additionally, 31% of liberal faculty think blocking students from attending a speech is sometimes acceptable, while only 16% of moderates and 5% of conservatives agree. One survey showed half of academics in the social sciences and humanities expressing a willingness to discriminate against Evangelical Christians in hiring decisions.

Fearing progressive ostracism, scientists avoid certain issues, especially race and gender, or only allow members of a victimized group to speak on a topic. Cathy Young writes, “Researchers and clinicians who depart from the orthodoxy on youth gender dysphoria have been targeted by intense pressure from activists, leading to severe career repercussions and, in one case, the retraction of a large study of adolescent ROGD [rapid onset gender dysphoria].” Thus, progressive-dominated academia and media ignore or suppress inconvenient information, such as the use of puberty blockers being questionable, data that as many as half of transgender female prisoners are sex offenders, or that key scientists were uncertain about the origins of Covid-19.

To the extent that progressives dominate knowledge-producing institutions and view conservatives as illiberal, they exercise institutional power to marginalize information that can be weaponized by those they consider harmful actors; this violates procedural liberal norms on objective scholarship and nonpartisan journalism. Conversely, to the extent that conservatives view mainstream institutions as biased and oppressive, they turn to alternative news sites and social media accounts that are disconnected from and even hostile to mainstream institutions, with these sources usually lacking traditional journalistic procedural norms and practices used to distinguish between corroborated and non-corroborated claims. Alternative media popular with MAGA Republicans such as X and Truth Social offer both true information suppressed in mainstream institutions, and fake news and conspiracy theories, including those that come from Russian influence campaigns.

Mainstream media also disseminate some unsubstantiated claims such as hidden mass graves of indigenous children, but the dissemination of misinformation, without basic fact checking procedures, occurs at much higher rates in conservative and alternative media.

Finally, to the extent that partisans access mutually isolated information markets, they diverge in their worldviews and policy preferences. If the information market on one side is flawed, partisans advance policies based on false assumptions. Some of the Trump Administration’s steps taken on Ukraine, tariffs, and DOGE budget cuts, among other topics, exemplify reliance on false information, such as that President Zelensky is at a four percent approval rating.

The pattern of asymmetric polarization and diverging (mis)information between the progressive-dominated mainstream and the conservative alternative is replicated in other OECD countries such as Germany. As in the US, the far-right media in Europe disseminates more misleading and uncorroborated claims than do mainstream outlets.

In South Korea, asymmetric polarization is both more illiberal, as conservative and progressive partisans use legislation and judicial rulings to imprison opponents who challenge their favored narratives; and unique, as the progressive-dominated mainstream matches the ‘far-right’ alternative in disseminating unsubstantiated claims, and only the progressive mainstream disseminate such claims from their autocratic neighbor, in this case China, and censor serious academics.

Even more than in the US, the major parties in South Korea divide over the legacy of the nation’s major founding presidents: Rhee Syngman (1948-1960) and Park Chung-hee (1961-1979). Conservatives, led by the current People Power Party, generally laud the founders’ opposition to communism, and communist-party led North Korea and China, and support of the US and free market capitalism. Conversely, progressives, led by the Democratic Party, strongly criticize the human rights violations and social injustices associated with the founding administrations’ anticommunist and pro-capitalist policies, and support those more favorable to labor unions at home and to North Korea and China abroad.

Since South Korea’s first leftist government, that of Roh Moo-hyun (2003-08), the communist-capitalist divide has overlapped with another one based on religion. Many Korean Evangelicals laud the Christian values of founding President Rhee, and oppose same-sex marriage and other challenges to traditional family values. Conversely, progressive Presidents Roh and Moon Jae-in (2017-22) have appointed judges who support the rights of historically victimized groups, including members of the LGBT community.

Before democratic reforms and the political transition of the 1990s, conservatives used their dominance of the government and media to frame their opponents as pro-North Korea leftists and collaborators. They vigorously enforced the 1948 National Security Law’s Article 7 prohibition against pro-communist speech to silence progressives.

Since the 1990s, however, progressive partisans have effectively promulgated an equally Manichaean narrative of the Rhee and Park regimes, and their conservative successors, as pro-Japan collaborators and authoritarian fascists. Korean progressive media producers partner with US providers of content like Apple TV and Netflix to globally disseminate narratives that dramatize or fantasize the evils of the Japanese colonial (1910-45) and anticommunist regimes (1947-1987), which effectively stigmatize pro-Japan or anti-communist viewpoints and justify their legal suppression. Works in this genre include the film Exhuma (2014), and the series Mr. Sunshine (2018-) and Taxi Driver (2021-).

Although progressive icon Kim Dae-jung praised free speech, his successors in the Democratic Party have used their growing political and judicial influence to punish speech that defames former victims of colonial or authoritarian regimes, including obtaining a six-month prison sentence for Song Dae-yup, a professor who suggested that most Korean comfort women had volunteered for the Japanese military and two years for Jee Man-won, a commentator who claimed that North Korea helped direct rioters during the 1980 pro-democracy movement in Gwangju.

In December 2020, the DP-dominated Assembly passed the May 18 Distortion Punishment Act to imprison up to five years those who make false claims about the 1980 movement. If progressives regain the presidency, they promise to extend the Act to cover “false” claims, including those about North Korean agents, in other democratic uprisings.

By suppressing supposedly harmful far-right or pro-Japanese viewpoints and information, progressive-dominated media and schools become an echo chamber of uncorroborated claims, such as that the Japanese military kidnapped as many as two hundred thousand Korean girls and that North Korean government agents did not communicate with democracy activists, and that arguments to the contrary are those of fascists.

Korean academia and media such as the Korea Times and Hankyoreh also partner with government-controlled institutions in China. In 2014, China’s Jilin Provincial Archives provided the South Korean media with 25 documents showing that the comfort women did not sign up voluntarily in order to make money – as Japan claims – but had actually been officially mobilized by the Japanese imperial army. US-based academics and journalists repeat the sexual slavery narrative and ostracize dissenting scholars such as Harvard Law School’s Mark Ramseyer.

Korea- and US-based academics support South Korean legislative efforts to further criminalize far-right speech. They even target creative fiction: in 2021, activists pressured corporate sponsors to drop the Disney plus television show Snowdrop because of its fictional portrayal of a North Korean spy during South Korea’s democracy movement in the 1980s. US-based mainstream media have supported such activists by labeling claims about North Korean involvement as “conspiracy theories”, despite some documented evidence. Kookmin University historian Andrei Lankov writes that he “personally knows [three] people who once commuted to Pyongyang via submarine” (Lankov, The Real North Korea, p. 31).

Shaped by progressive-dominated, knowledge-producing institutions, Democratic Party leaders condemn scholars who challenge the progressive narrative. After Sejong University professor Park Yu-ha published her book, Comfort Women of the Japanese Empire, which won top academic awards in Japan, Democratic Party chief Lee Jae-myong posted the following on Facebook

This professor…
Is she still holding her position as a professor?
How did I end up breathing under the same sky as someone like her… sigh.
These remnants of pro-Japanese collaborators must be cleared away.

Since former conservative President Park Geun-hye’s 2016 impeachment, the Democratic Party has dominated the National Assembly. Yoon, the conservative party candidate, barely won the 2022 presidential election, but the DP parliamentary majority paralyzed the administration with an unprecedented array of budget cuts, along with 22 motions to impeach government officials, before Yoon declared martial law on December 3, 2024.

To justify such paralysis, DP partisans framed the Yoon Administration’s policies of reconciliation with Japan as pro-Japan collaboration. The initial December 4 impeachment motion stated: “Yoon has neglected geopolitical balance, antagonizing North Korea, China, and Russia, adhering to a bizarre Japan-centered foreign policy, and appointing pro-Japan individuals to key government positions.”

Grassroots conservatives, in turn, rejected mainstream media, whose “fake news” defamed their political heroes as pro-Japan collaborators, whether former Presidents Rhee Syngman and Park Chung-hee or current President Yoon. Instead, they turned to social media, especially YouTube, which has become a primary source of information for 53% of South Koreans, including 70% of right-wing rally participants. By disconnecting from mainstream media, conservative media became an echo chamber of uncorroborated theories, such as that progressive lawmakers are secretly collaborating with North Korea or that North Korean hackers infiltrated the National Election Commission.

In the aftermath of the December 3 martial law declaration, grassroots conservatives praised President Yoon for performatively standing up to the Democratic Party and drove out institutional conservatives who disagreed. After resigning as PPP chief on December 16, Han Dong-hoon warned party members, “If we sympathise with extremists like the conspiracy theorists and extreme YouTubers, or if we are consumed by their commercially produced fears, there is no future for conservatism.”

Even as institutional conservatives felt excluded in their party by radicalized conservatives, they felt excluded in mainstream, knowledge-producing institutions by dominant progressives. CM, a female graduate student at a Seoul-based university, criticized the May 18 Act:

Asking a question like “Aren’t they rioters?” is not allowed despite the fact that protesters during the May 18 Gwangju Uprising broke into armories and armed themselves with stolen weapons and ammunition. Some people around me argue that the May 18 Special Act suppresses freedom of expression. I would go further and say that it is a draconian law that also suppresses the freedom to seek the truth.

PJ, a male graduate student, opposed Yoon’s martial law declaration as “too radical,” but also opposed the National Assembly’s swift impeachment of the president, before any police investigation or assembly hearing. PJ preferred the months-long process of investigation and deliberation that led to bipartisan consensus on President Nixon’s resignation. But he declined to openly voice this argument in his university, fearing not just condemnation from progressive faculty and student groups, but also imprisonment from a future DP administration. In his view, DP-appointed judges could interpret existing defamation laws, or legislators might pass a new law (“December 3 Act”) modeled on the May 18 Act, to criminalize statements justifying Yoon’s “fascist” martial law declaration.

Korea-based conservatives such as PJ risk more suppression, including imprisonment, for expressing their views than do American conservatives. But unlike their US counterparts, Korean conservative radicalism was largely limited to supporting President Yoon’s (allegedly) performative, and brief, martial law declaration. They have not yet sought to defund and dismantle mainstream, knowledge-producing institutions (e.g., the education ministry, national research foundations, elite universities), as in the US . Neither do conservative Korean students reject elite universities in favor of conservative alternatives like Hillsdale.

Influenced by Confucian norms, practically all Koreans, conservative or progressive, valorize elite, mostly Seoul-based, universities such as Hanyang and higher-ranked universities abroad. Like the older, Bush-style Republicans in the US, Korean conservatives desire mainstream institutions to be more open to conservative perspectives, not to destroy them. Unlike many MAGAs, most Korean conservatives do not consider reforming the elite universities or the education and scientific ministries to be a lost cause, but a worthy even if difficult mission.

A key difference is that matriculation into elite Korean universities, major newspapers, and government bureaucracies is predominantly determined by standardized exams, not subjective and politicized essays, letters of recommendations, and extracurriculars. Seemingly non-meritocratic, Claudine Gay-style educational elites do not exist in Korea. Therefore, Korean conservatives challenge the progressive majority, but not the core legitimacy of mainstream institutions.

Among OECD democracies, the US and Korea exemplify the challenges of polarization and especially asymmetric polarization. Progressive dominance of mainstream information sources does not justify the self-imposed isolationism and disruptive radicalism of conservatives, culminating in the December 3 martial law declaration in South Korea and the defund, dismantle, and deportation agenda of the second Trump Administration. But it does help us understand that conservatives’ procedural illiberalism and misinformation, and policies based on such misinformation, do not appear in a vacuum, and that any infringements of liberal-procedural norms can polarize and destabilize democracy.

Breaking this cycle requires not more suppression or radicalism, but reaffirming the liberal-procedural norms of open debate and respect for legal rules and customs.

On December 22, then President-elect Trump announced the appointment of Sriram Krishnan, a successful venture capitalist, as a senior adviser on artificial intelligence. A model immigrant, Krishnan came to the US at 23 to work at Microsoft, later becoming a naturalized citizen. What should have been a discussion of AI policy and a celebration of the success of high-skilled immigration soon turned into a civil war on the right, after nationalist influencers highlighted Krishnan’s past comments endorsing more high-skilled immigration. The H-1B visa program became the focus of the debate, which exposed a deep division among the Trump coalition, between the techno-libertarians led by Elon Musk and the national-populists led by figures like Steve Bannon. Trump eventually came out in favor of the H-1B visa, but it remains to be seen what his administration does on this issue.

At the heart of the objection by the national-populists are arguments based on what economists have called the “fixed pie fallacy,” but in this case can be referred to as the “lump of labor fallacy.” “It’s about taking American jobs,” Bannon has claimed. “A tech company used the H-1B visa to replace [American workers],” JD Vance bemoaned when criticizing the visa as he was running for Senate in 2022. From the other side of the political spectrum, Bernie Sanders chimed in against the program, arguing it replaces “good-paying American jobs with low-wage indentured servants from abroad,” forming an unholy alliance of socialists and nationalists.

According to this logic, there is a set, or at least highly inelastic, number of jobs in the United States. This is true in tech, just like it presumably is in other fields like retail or oil extraction. If more people are allowed in the country, then more Americans are going to either be unemployed or expect much lower wages for their work.

This fallacy has long been known to economists. Adam Smith in The Wealth of Nations (1776), challenged zero-sum assumptions prevalent in mercantilist theories. Later, David Ricardo and John Stuart Mill further explored how trade, innovation, and productivity could expand the economic “pie.” And in the 20th century, President Reagan’s economic guru Milton Friedman famously taught that “most economic fallacies derive from the tendency to assume that there is a fixed pie, that one party can gain only at the expense of another.”

Yet this is not how the economy works. Newcomers do in a sense compete for jobs within one industry. But they also buy homes, food, clothing, and shelter within the United States. If employers prefer the labor of immigrants, whether due to them being better workers, cheaper, or some combination of the two, then it must mean that firms are likely to become more efficient after hiring them, further stimulating economic growth. If a tech firm pays less money for labor, even assuming no gain in efficiency otherwise, they do not simply burn the money but invest it or put it back into the economy by returning it to shareholders. Even if all the savings go to CEO compensation, and executives spend that money rather than place it in the stock market, this still increases demand in the economy.

The lump of labor fallacy assumes that the demand for labor is static: there is a set number of jobs and that introducing more workers must reduce employment opportunities for those already in the workforce. American history is filled with counterexamples. When the US gradually allowed women into the workforce, it didn’t cause massive job losses among men; when segregation was abolished in the South, black workers didn’t cause mass unemployment among whites; when the 13 colonies established free movement of people among the states with the Articles of Confederation in 1781, this did not cause economic upheaval. The vast majority of native-born Americans are descended from immigrants, including the national-populists vehemently opposed to H-1B visas. Did their ancestors take away American jobs? Or did they contribute to the economy by working with the natives?

Even setting aside their roles as consumers, what restrictionists fail to realize is that high-skilled immigrants not only take existing jobs, but create new ones by becoming entrepreneurs themselves. The most salient statistic is perhaps the fact that 45% of Fortune 500 companies were founded by immigrants or children of immigrants. In AI, a report from the National Foundation for American Policy concluded immigrants also founded or co-founded 65% of the top companies. Elon Musk, maybe the greatest entrepreneur in history, was once on an H-1B visa. All of this has happened in spite of the restrictiveness of the immigration system. In many ways, high-skilled immigrants are the lifeblood of American innovation. Even low-skilled immigrants, by taking the most unglamorous and unpleasant jobs, enable natives to be productive in other ways by lowering the costs of labor. One may have other arguments against immigration, but the economic case based on a fixed number of jobs makes no sense.

The fixed pie fallacy fails not only in the context of the labor market. As alluded to above, immigrants raise demand for goods and services, including those that natives are uniquely positioned to provide, such as education, legal services, entertainment, and management. If the pie were truly fixed, a virus that randomly killed half of Americans would make everyone twice as rich.

Housing is an area where the pie is close to being fixed in many regions, but this is only the result of zoning laws that restrict supply. There are an endless number of reasons why we should make housing easier to build, and the payoffs to doing so are potentially massive. But to restrict immigration on that basis alone would mean responding to one broken policy by hurting the economy in another.

What all this means is that not only are H-1B workers highly-paid, with median earnings at around the 90th percentile of wages, but each H-1B worker is estimated to create 1.83 jobs for native-born Americans. This is not surprising at all. As high earners, H1-B recipients must be a net benefit to the economy. In no other context would anyone argue that workers in the top decile of productivity are making Americans poorer.

Callum Williams, senior economics editor at The Economist, has argued that having a much larger common market goes a long way towards explaining why Americans are so much wealthier than Europeans. In a tiny village where individuals only trade with members of their own community, compared to a large developed country, it is less likely there will be enough demand to make being the owner of a boutique bookstore, a Substacker, or an exterminator a realistic career path. This is why, for example, American restaurants will commonly have different jobs for hostesses and waiters, while in Europe one employee will take on both roles. More people means greater economies of scale. When newcomers are well above average in productivity, as H1-B recipients are, opening the borders to them becomes a no-brainer.

What if you only wanted to focus on wages for tech workers? One might acknowledge that highly productive workers making businesses more efficient are good for the economy as a whole, but can we at least say that a certain class of worker they compete with is worse off?

That is far from certain. Noah Smith has an excellent recent summary of papers arguing that H-1B visas don’t even hurt workers that are in direct competition with new arrivals. We have a strong basis for believing this because H-1B visas are distributed based on a lottery system, so we can treat the process as a random experiment and see what happens to the wages of individuals working for firms that win the lottery versus those that don’t. Workers in the firms that get immigrant labor end up hiring more tech workers and paying them more, because they become more efficient and sometimes scale up.

Of course, immigration policy shouldn’t be determined on the basis of what is good for workers in one industry, but what is good for the nation as a whole. So even if you do not find such studies convincing, you should want more productive workers to come into the country because a welcoming policy still makes society better off. This is not controversial among economists, as the question gets to the basic assumptions of their field. A 2016 poll of economists showed exactly 0% disagreeing with the idea that letting employers hire more immigrants with STEM degrees would raise per person income in the US in the long run.

To be fair, an overwhelming majority also said that such a policy would at least temporarily lower the premium earned by workers with similar degrees. However, it must be noted that this survey was conducted before most of the studies cited by Noah Smith in his recent article. It would be interesting to see what economists who are familiar with the literature that has come out over the last few years think. But, again, even if it is true that immigrants directly suppress the wages of workers they compete with, public policy being designed to help subsets of society rather than the entire country is the path to stagnation. If we try to “protect” the workers in every industry from competition, we will all end up poorer.

Unfortunately, zero-sum thinking tends to be common when individuals consider economic issues. People often misjudge market interactions as win-lose rather than win-win, especially when foreigners are part of the equation. Irresponsible politicians and pundits take advantage of such biases, demagoguing bad policies into existence, to the detriment of society.

Yet letting in more immigrants is not a form of charity on the behalf of Americans. It’s an arrangement that expands the pie, benefiting both newcomers and natives. America is blessed with being the top talent magnet in the world. It would be a shame to waste one of its greatest assets.

Does higher education value policy and administrative reforms likely to save black (and ideally other) lives? Or does higher education care more about virtue signalling and promoting a broad leftist agenda to enhance the power and status of academics and their institutions, whatever the impacts on most other human beings?

The genesis of this essay can be found in a 2019 academic conference in which one of us (Maranto) presented a paper, later published in Public Integrity,1 which ranked police departments in 21 of the 25 largest US cities by their success in 2015 in keeping homicide rates low and not killing civilians, while adjusting for poverty rates, since high poverty makes policing more difficult. The New York City Police Department (NYPD) topped the rankings, with very low homicide rates and the lowest rates of police killings of civilians despite the city’s relatively high poverty. (Our 2020 analyses of 50 cities again ranked NYPD first.) As with other attempts at bureaucratic reform, ranking police departments based on their success on these important metrics has the potential to drive improvements by encouraging less successful cities to copy their more successful peers. Since both police killings of civilians and much more common civilian-on-civilian homicides disproportionately take black lives, progress on these indicators would indeed make black lives matter.

Almost any American without a PhD can see the value in this kind of research. But as recounted by one of us in the Wall Street Journal,2 other social scientists at the 2019 conference expressed confusion and at times astonishment as to why anyone interested in Black Lives Matter might study ways to improve policing. Instead, BLM researchers were interested in using the movement to increase progressive power. As of June 2020:

Using Google Scholar, the five most cited research articles and book chapters with “black lives matter” in the title include “a herstory of the #blacklivesmatter movement,” an article on “the evolving role of social media,” another on “mass struggle,” a commentary on racism and public health, and a piece on environmental justice. Other widely cited works study news coverage of the movement, youth activism, and the “migrant crisis” in Europe. Judging by their titles, none of the twenty most cited articles or chapters on Black Lives Matter directly seek ways to reduce police killings of black civilians.3

Similarly, as of May 5, 2022, there was just one Web of Science citation for Franklin Zimring’s 2017 When Police Kill,4 a serious empirical analysis suggesting ways to reduce civilian deaths at the hands of law enforcement. This (mis)allocation of research effort reflects the takeover of large sections of the social sciences by critical theory supporting activists seeking power (and grant funding), who are relatively uninterested in seeking to understand and ameliorate social problems like violent crime and police brutality.5

Here we repeat the June 2020 Wall Street Journal analysis in a somewhat different way, focusing not on titles but, instead, on generating rankings by conducting a general keyword search on the Web of Science Core Collection for “black lives matter” and sorting by publications with the most citations as of April 20, 2022.6 The Web of Science is more restrictive than Google Scholar, yielding far fewer citations, in our experience over 95% fewer.

The 25 most cited works listed in the above table have a combined total of 1,704 citations. As in the 2020 search using Google Scholar, the vast majority of the Web of Science citations seemingly have little to do with either studies or commentary likely to save black lives. At least from their titles, the top five works, those with 98 or more Web of Science citations, resemble, and often are, the most influential publications of 2020 using Google Scholar, involving public health, millennial activism, and the migrant crisis in Europe. In addition, the second most widely cited piece discusses how political science as a field treats marginalized communities of color.7 As its authors explain: “Focusing on policing, we seek to unsettle the mainstream of a subfield that rarely inquires into governmental practices of social control and the ways ‘race-class subjugated communities’ are governed through coercion, containment, repression, surveillance, regulation, predation, discipline, and violence.” Such analyses seem unlikely to decrease either homicide or police violence against civilians. They are unlikely to help make black lives matter on this planet in any foreseeable time frame.

Generally, the highly cited articles listed in the table explore social media use and activism (4, including one piece involving Ben and Jerry’s ice cream and BLM), racial activism and white attitudes (3), immigration and migrants (2), anti-Blackness in higher education, “democratic repair,” radically re-imagining law, anti-Blackness of global capital, urban geography, counseling psychology, research on K-12 schools, BLM and “technoscientific expertise amid solar transitions,” BLM and “evidence based outrage in obstetrics and gynecology,” and BLM and differential mortality in the electorate. Again, we see little evidence of author (or citer) intent to save black lives in the works that frequently get cited.

Of the 25 most cited scholarly articles, only one, ranked 19th, from Public Administration Review, presents research that has the potential to save black and other lives in ways that are relatively immediate and related to law enforcement. It is titled “Preventing the Use of Deadly Force: The Relationship between Police Agency Policies and Rates of Officer-Involved Gun Deaths.”8 This fascinating article uses cross sectional data from 1,107 law enforcement agencies over 15 years, standardized by population. The authors, Jennings and Rubado, find no evidence that either community policing or having police officers who demographically resemble their cities reduces the number of fatal police shootings of civilians. In contrast, roughly half of departments require that officers file a report whenever they point their guns without shooting. (Virtually all require such reports when weapons are discharged.) Empirical evidence indicates that this simple reporting requirement substantially reduces police shootings of civilians, while managing not to increase shooting deaths of officers.

Most proper science is tentative, and sometimes reforms have unintended consequences. That said, the paper empirically evaluates practical ways to save lives, prescribing a reform with the potential to do so. This article accounts for just 44 (2.6%) of the 1,704 Web of Science citations of the 25 most cited articles found in the “black lives matter” keyword search. The Bearfield, Maranto, and Wolf9 ranking of large police departments to identify those most successful at preserving life was cited just twice by Google Scholar as of May 2022 and not at all in the Web of Science. We doubt this article will ever rank among the top 1,000 cited BLM-related publications.

One force that sets a positive example other cities could follow is the aforementioned NYPD. Each year, its internal affairs division pushes dozens of officers to resign, retire early, or move to routine administrative duties like vehicle impoundment in which they are unarmed. Others are prosecuted, as longtime NYPD Internal Affairs Bureau Chief Charles Campisi documented in his lively Blue on Blue: An Insider’s Story of Good Cops Catching Bad Cops.10 An NYPD source indicates that about 300 officers, nearly 1% of the force, are on internal watch lists. When told that NYPD should feel satisfied having so few problematic officers, the source retorted that they had trouble sleeping at night since every one of those officers presented a “potential” George Floyd or Freddie Gray “situation.” In retrospect, Minneapolis and Baltimore might have been better off had more of their police administrators thought this way. Two years after the Floyd murder, observers believed that, along with civil service rules, the Minneapolis police union contract still posed undue burdens on police managers who wanted to hold their officers accountable.11

In short, much can be done to improve policing in ways that would make all lives, but especially black lives, matter. Alas, currently, we cannot much rely on academia to help. If anyone intends research to save black lives rather than merely to promote radical causes and the careers of professors, then we need a major reorientation of social science research, and arguably, of the whole higher education enterprise.

The new brigades are trained and ready to go — reports vary, but there are maybe a dozen or so, plus replacements to replenish existing units. Anywhere from 40-60,000 fresh troops trained in combined arms maneuvers are ready to join the fight. They largely have old equipment; Ukraine has given its new Western armor to its most experienced units, intending them to spearhead the assault. At the same time, Ukraine’s spring muddy season has lasted unusually long this year. But the weather has gradually warmed over the last month, the rains are becoming less frequent in Luhansk, Ukraine is launching probing counterattacks along the front line, its strikes on Russian supply lines are picking up, and the ground is beginning to dry.

But maybe not: as I write, the weather forecast now predicts significant rain in the week ahead, especially in the Zaporizhzhia region, possibly muddying things up again until mid-June. We’ll see. The mud is basically the one thing Ukraine is waiting on at this point. The Ukrainians won’t launch suicidal assaults plowing their tanks into deep mud just because internet observers are itching to see action.

Since Ukraine is likely to make a major move within the next month or so, this is an opportune time to assess what to expect in the near future, explain why I think Russia is finished as an offensive force, and lay out Ukrainian strategic options.

The Stakes

Throughout this war, we’ve seen a number of illustrations of Clausewitz’s maxim that war is the continuation of politics by other means. Ukraine’s looming counteroffensive has two major goals: first, reclaim territory from Russia, and second, be seen to do so in order to sustain Western support.

This has clearly become a proxy war between Russia and NATO, supercharging the political considerations inherent to any war. Ukraine’s goal is to wheedle as much military aid as humanly possibly out of NATO, especially the United States. The United States’ goal is more complex: give enough aid to push Russia back, but not so much that its proxy war with Russia escalates into an actual one.

This dynamic has created a Hunger Games scenario where Ukraine is constantly playing to the cameras to cajole extra gifts from the wealthy sponsors who watch its every move over the internet in real time. I had decided against using this analogy until I saw Ukrainians themselves using it. There is something grotesque and sobering about finding yourself in this position, and writing about it. But it is what it is.

A certain strain of America First politician views every bit of aid to Ukraine as something that could’ve been spent on their preferred hot-button issue instead. They can be identified by pleasing soundbites like “Why are we worried about an invasion on the other side of the world when our own border is being invaded right now?” and “Why is Biden visiting Kyiv when he won’t even go to East Palestine?” Joe Biden supports Ukraine so they don’t; if Biden hated Ukraine, they would be its best friends. Ron DeSantis cozied up to this crowd when he called the war a territorial dispute that the US had a limited interest in. The Wall Street Journal immediately rebuked him, reminding conservative politicians that even now, pandering to a vocal minority only goes so far.

Some suggest we should cut Ukraine off to focus military resources on China. This overlooks the fact that aid to Ukraine largely doesn’t compete with aid to Taiwan since the former involves a ground war and the latter conflict would mostly be fought by air and sea. The only pieces of equipment Ukraine and Taiwan directly compete for are Stingers and Javelins. Some have suggested HIMARS can be adapted to shoot at naval targets, but the system recently performed very poorly in a test of that role in the Philippines. What Ukraine needs most are armored vehicles to help assault fortifications and protect its troops from shrapnel — since most casualties are caused by artillery, infantry fighting vehicles may be even more important than tanks.

The US has almost 7,000 Bradley fighting vehicles sitting in storage. It spends money maintaining them and plans to scrap them eventually. Bradleys can kill anything on the battlefield pretty easily and ferry a squad of infantry around while doing it, protecting them from artillery shrapnel. When the Biden administration slaps a price tag on them, ships them to Ukraine, and lets them kill Russians without Americans dying, it’s not actually spending any money. We could give a thousand Bradleys to Ukraine and not notice they were gone.

The cold hard truth the America First crowd’s simple algorithms overlook is that sending spare armor to Ukraine is a good deal for America. This is why Russia accuses the US of planning to fight it to the last Ukrainian, and why some Ukrainians suspect the US limits aid to the level that would most drain Russia. Biden’s refusals to send fighters and long-range missiles are probably more about managing escalation risk by respecting Russian red lines, but the suspicion is understandable. He’s slow-cooking Russia by escalating aid gradually.

There are more nuanced skeptics Ukraine has to contend with as well. Some fear the war may bog down into indefinite static trench warfare that accomplishes nothing but draining resources and lives on all sides — a view I’m sympathetic to, though I don’t think we’re at that stage yet. If the coming counteroffensive achieves little or its gains are quickly lost, that will suggest the front lines have become static and Ukraine will lose support. That doesn’t mean it will be cut off; it simply means it will receive only the aid necessary to prevent Russia from advancing. NATO will pressure it to go to the negotiating table and give up Crimea and part of the Donbas.

I suspect that’s how this war will end, and the remaining fighting is about seeing how far Ukraine can advance to determine how much of the Donbas it has to give up, along with the fate of Zaporizhzhia — the eventual settlement may involve Ukraine trading some of the Donbas to reclaim territory in the south. Finland had to cede 9% of its territory to the Soviet Union to end the Winter War in spite of inflicting a lopsided 5:1 casualty ratio on its larger neighbor.

Ukraine has powerful backers, but the president has shown no indication he’ll give it enough support to retake Crimea and the entire Donbas (for an alternative view, see here). It’s easy to criticize Biden, but the truth is that he’s managed the risk of nuclear and conventional escalation successfully so far. Whatever mistakes he’s made elsewhere, in Ukraine, Biden has demonstrated the value of having a steady hand at the wheel. Notice that the nuclear bluster has died out now that India and China have told Russia it'll lose its only friends if it uses nukes.

So these are the stakes of the counteroffensive: Ukraine must be able to point to significant territorial gains to justify continued offensive military aid. Its task is to grab as much as possible before its Western backers decide the war has bogged down and force it to the negotiating table. There is a vast pool of armored vehicles of all kinds available, and Ukraine can keep getting more as long as it keeps proving it can advance with them.

The Status Quo

Russia’s winter offensive has failed. It ended autumn by throwing untrained conscripts at the front lines to prevent Ukraine from extending its Kharkiv counteroffensive to Luhansk. Russia succeeded in stabilizing the front there. But to justify the cost of war and mobilization to its populace, it then attacked into the teeth of the Ukrainian defense in the dead of winter. The results were predictably disastrous.

Russia began by dashing its best units against the fortress city of Vuhledar. It made marginal gains in Luhansk, pushing the front back slightly from Svatove and Kreminna but failing to reach the strategic targets of Kupiansk and Lyman. Little happened in Zaporizhzhia, other than both sides digging in. Desperate to show its population some victory, any victory, Russia concentrated its remaining efforts on taking the small city of Bakhmut.

The amount of ink and blood spilled over Bakhmut would make you think it’s strategically significant, but nothing much hinges on it. Each side is fighting bitterly because the other wants it. For Russia, the strategic value of Bakhmut is that it gets it one step closer to the actually valuable cities of Kramatorsk and Sloviansk. But it’s not as if taking Bakhmut would put it at their doorstep; Ukraine has had all the time in the world to prepare layers of fortified lines between them and Bakhmut.

A month or so ago, when Zelensky was asked why he was spending so many lives defending Bakhmut, his answer was if Russia takes it, it’ll be one step closer to Kramatorsk. Well, yes, that’s a truism. What is actually going on is that Ukraine has been happy to whittle away Russian forces with the defender’s advantage as long as Russia has been happy to keep assaulting Bakhmut. Estimates of casualty ratios vary, with Ukraine claiming an unrealistic 7:1 at one point. 4:1 or so overall seems possible given Wagner’s human wave tactics, with the ratio more even toward the end of the battle. Pentagon officials recently claimed Russia has suffered around 20,000 dead and 80,000 wounded since January, with the lion’s share probably occurring as it fed men into the meatgrinder at Bakhmut.

Ukraine kept defending Bakhmut to make Russia keep attacking instead of digging in. As I write, it seems Russia has finally captured virtually all of the city. In the months since I’ve started commenting on the war, I’ve always said I don’t think much hinges on Bakhmut. I won’t think it matters much if Ukraine retakes it, either.

Russia’s offensive capacity is now spent. Its best tankers died in Kharkiv and Luhansk. Its best marines died at Vuhledar; its best mercenaries died at Bakhmut. Its best human shields died at Bakhmut. It squandered its elite paratroopers, the VDV, throughout the war, using them as regular infantry units to make marginal gains whenever its actual infantry failed. It used its Spetznaz as regular infantry too and now most of them are gone.

Why have Russian advances stalled? Why does it have one small city to show for the last half year of war? At this stage of the conflict, Russia’s best men are dead. Its best equipment has been destroyed. It cannot replace those units with untrained conscripts manning 70-year-old tanks. I predict that no number of mobilizations will allow it to make meaningful gains going forward. Russia will never reach the walls of Kramatorsk. It probably won’t even retake Lyman.

You might notice I’ve said nothing about the air war, which gets a disproportionate amount of media attention and is where Russia has had its greatest successes over the winter, draining Ukrainian air defense ammunition. The Iranian Shahed drones have been very efficient; it’s a win for Russia every time Ukraine uses a missile to shoot one down.

You could write an entire piece on nothing but the air war. Ukraine appears to now be shooting down nearly 100% of Russia’s missiles and drones attacking Kiev, a startling use of resources considering how low its air defense supply is said to be. It’s either being foolish or it has more than people think — didn’t those leaks say their supply was supposed to be empty by now? If it’s being stupid, we’ll know soon. It seems to be shooting down a fair number of Russian fighters and bombers lately.

We have Patriots reliably shooting down hypersonic missiles, which no one predicted — that may give China some pause — and Germany sending 15 more Gepards, the best anti-drone defense there is, as well as a large package of air defense batteries. F-16s will probably start arriving within the next few months. How will Ukraine’s supply of NATO air defense ammo fare against Russian missile and drone supplies? I’ll bet on the bigger economy winning in the end, that is, the western alliance, but I won’t give any further analysis here. Each country’s ammo supplies are a black box, a jealously guarded secret, while GDP is not.

The air war is important. But the armor supply is what will be decisive in the long run. Ukraine asks for F-16s, but what it needs is 500 Bradleys. This war is now about how much Ukraine can advance. Russia is finished as an offensive force.

Ukraine Has a Growing Advantage in Modern Equipment

The news media is obsessed with missile attacks and minor happenings in Bakhmut because that’s where the news is. You can only write so many articles about NATO’s armor supply. But that’s what matters. Some have called this a war of attrition. That might mislead you into thinking Russia’s 4:1 population advantage will be decisive. I would call it a war of attrition of trained troops and modern equipment. This is the foundation of my confidence in Ukraine’s prospects.

As the war goes on, Ukraine’s equipment gets better and more of its soldiers complete Western training. There is an essentially unlimited pool of quality IFVs and APCs available — the US alone has 4,000 Strykers I haven’t mentioned yet — and there are 2,000 Leopard 2s floating around Europe that it’s been stingy with so far. To be fair, it’s not just stinginess. NATO’s supply of modern armor is virtually infinite; the bottlenecks are in logistics and training. You have to train the mechanics, too. Now that the first wave of Ukrainians has completed training on modern equipment, the train-the-trainer model should allow the West to send more, perhaps exponentially more. I expect that hundreds more Bradleys and Strykers are coming soon.

Meanwhile, Russia’s equipment keeps getting worse. It sent many of its trainers to fight on the front lines back when it believed the war would be short. As Ukraine upgrades with Bradleys and Leopard 2s, Russia is replacing T-72s with T-54s. I believe that as the war progresses, we will enter a vicious cycle where Ukrainian veterans manning modern armor slaughter waves of Russian conscripts. The rich will get richer in experience and equipment and the poor will become poorer. The bottomless supply of NATO armor means that Ukrainian soldiers, unlike Russian ones, will get to live long enough to learn. They’ll survive artillery shrapnel.

Writing for Forbes, David Axe has an excellent series of articles documenting the progression of this war of attrition of modern equipment. To my knowledge, he is the only mainstream reporter tracking this important element of the war. One example of the equipment attrition war is night vision: Russia is running very low on modern optics to upgrade old tanks with. Ukraine will increasingly have the advantage when fighting at night. It will be increasingly able to outsee, outmaneuver, outrange, and outshoot Russia.

Below is a summary of Oryx’s list of heavy weaponry supplied to Ukraine for the counteroffensive. I’ve supplemented it with information from other sources on when pledged equipment is expected to arrive soon.

As I wrote this, Germany announced its largest aid package yet, valued at nearly $3 billion. I tried to include it, but Oryx’s list may not be fully updated; the artillery doesn’t seem to be reflected yet. The pledge of 20 more Marders, 30 Leopard 1s, and a hundred unnamed armored vehicles (not included in the list above) suggests this may be the beginning of the second wave of armor I expect, now that Ukraine can use some of its trained troops to train others. Word is that France is planning to send another tranche of AMX-10s too, basically light tanks. My training-bottleneck theory will be substantially falsified if the US fails to send more Bradleys or Strykers within the next couple months.

Potential Targets

“He who defends everything defends nothing.” As analysts speculate about where Ukraine’s hardest blows will fall, I keep remembering that famous quote from Frederick the Great. Right now, Ukraine is trying to make Russia think it could attack anywhere to make it try to defend everywhere. In the end, I think Ukraine should and will attack whichever place Russia chooses not to defend. I have an idea of where that might be. But I’ll describe other potential targets and the pros and cons of attacking them first, beginning with the most valuable.

To the sea

Strategically, the biggest prize would be for Ukraine to cut a path through Zaporizhzhia oblast all the way to the Sea of Azov. It hardly matters where. It’s not about taking cities like Melitopol or Mariupol. It’s about cutting Russian-occupied territory in two and winning Kherson, Zaporizhzhia, and Crimea without fighting for them.

If Ukraine managed to create and hold a corridor to the sea anywhere between the blue lines I’ve drawn, it would be a major coup. It would cut off Russia’s major supply lines to all territories to the west, limiting it to only what it could get through the Kerch Bridge, circled. Notably, the UK recently gave Ukraine Storm Shadow cruise missiles, which have the range and punch necessary to threaten the Kerch Bridge even from Ukraine’s existing positions. If Ukraine drives to the sea, Russia will probably lose both major supply lines to the west. It would lose its remaining holdings in Kherson, Zaporizhzhia, and Crimea without a fight. Disaster.

Of course, Russia knows this, which is why it spent all winter constructing multiple lines of defense in Zaporizhzhia. It may also be why this is one of the few regions it didn’t launch any attacks in; its troops there are the least bloodied.

The area to the north of Melitopol is a maze of fortifications. A couple other points are interesting. First, Russia has heavily fortified Crimea, too; it’s not clear to me why, since it would take Ukraine a long time to even reach it. As you can see, in the entire region of greatest danger Russia has fortified strong points along the highways in case Ukraine breaks through the front lines — note that it hasn’t done this in Donetsk or Luhansk. It has a cluster of defensive positions protecting its final fallback at the port city of Berdyansk, its regional headquarters. The Russian fleet can transport a limited amount of personnel and equipment back and forth from that port.

Russia is prepared to defend against a Ukrainian drive to the sea. This is why I think Ukraine won’t focus its efforts there. It may launch feints to keep Russia spending resources; it may even launch a big assault just to see if it can get lucky and break through. But if Russia commits appropriate resources to defend the south, as I expect it will, I doubt Ukraine will commit to a drawn-out slugfest attempting to force its way to the sea. It would be far too bloody and have no guarantee of success — exactly the conditions that might convince Ukraine’s backers to cut down on offensive aid.

The strategic prize in the south is far too risky. War is the continuation of politics by other means, and politics demands that Ukraine reclaim maximum territory with minimum losses. If I were Ukraine, I would continue to threaten Zaporizhzhia and Crimea to draw as many Russian resources there as possible and I would take out the Kerch Bridge to make the threat more credible and make it more difficult for Russia to supply the entire southern region. But I would not launch a counteroffensive in the south.

That brings me to happenings in Kherson.

Across the river

There have been rumors of Ukrainian footholds on the east bank of the Dnipro River for weeks now. Let’s cut to the chase: no, Ukraine doesn’t control any real territory there, nor is there much territory worth controlling. It’s a bunch of swampland. Ukraine may have recaptured a few islands in the delta that its commandos use as launching points for raids, joined by partisans sabotaging Russia behind its front lines.

This area is probably the least valuable of all the regions Ukraine might assault. Its value is instrumental to other objectives. First, if Ukraine launched a large attack across the river, it would hope to control the canal delivering water to Crimea from the reservoir at Nova Kakhovka, roughly outlined in blue. From there, it would hope to advance toward Crimea. This would very likely be intended as a secondary effort supplementing an advance toward Crimea from the Zaporizhzhia direction through Melitopol.

Again, Russia is perfectly aware of this danger; it’s built a series of strong points along all the highways from Kherson oblast to Crimea. I strongly suspect that Ukraine has achieved its real objective simply by getting Russia to spend time and resources fortifying this region. This is the westernmost area of the front and any troops either side sends here will be stranded far from wherever the actual fighting takes place. Ukraine is harassing the area to get Russia to divert as many men there as possible. Russia has to respect the threat; if it doesn’t defend against it, Ukraine may decide to take the opportunity to advance.

The bigger picture this fits into is that Ukraine has the benefit of short interior lines versus Russia’s longer exterior lines. Simply put, Ukrainian troops travel a shorter distance, and therefore quicker, whenever transferring between Kherson/Zaporizhzhia and Donetsk/Luhansk. It also now has higher-quality armored vehicles, potentially with better coordination. In the coming counteroffensive look for Ukraine to try to play ping-pong with the Russian army, attacking in one area to get Russia to divert forces there, then using its shorter interior lines to suddenly shift to the true target somewhere far away. Interior lines plus more maneuverable units are the force multipliers Ukraine will try to exploit to the fullest. Where will Ukraine attack? I predict this much: whatever it attacks first will probably not be its main target.

Encircling Bakhmut

It pains me to discuss Bakhmut. I don’t want to encourage the belief that the war hinges on it. But the city has some degree of importance simply because both sides have fought for it, as basically a random patch of ground they’ve agreed to duel on. Things have the value we assign to them, I guess.

It appears very likely that Russia has taken all of Bakhmut, in spite of Ukrainian denials. It is a sign of the myopic fixation on Bakhmut that people debate whether Ukraine still holds a few streets as if the question matters in the slightest. For a good take on the Pyrrhic nature of Russia’s victory, read this assessment from Igor Girkin, former commander of the DPR’s forces. I learn a lot from following his commentary and Russian media, especially Vladimir Solovyov’s show. Russian media has consistently become more pessimistic over the course of the war. Julia Davis is invaluable for her daily translations of Russian talk shows.

Zelensky would have people believe that Bakhmut is some geographic natural fortress that serves as the lynchpin of the Donbas; he said as much when justifying Ukraine’s continued defense. Interestingly, nothing could be further from the truth. Bakhmut sits at the bottom of a valley.

Remember when things got particularly dicey for Ukraine a couple months ago and it was nearly encircled in Bakhmut? Russia had seized the high ground to the north and south and surrounded it on three sides, shelling it from above. The two sides now appear to be trading territory.

Ukraine has captured around 20 square kilometers on the northern and southern flanks of Bakhmut. Some reports indicate that Russia withdrew Wagner and VDV units from the flanks to complete taking the city proper and replaced them with poorly-trained regular units that ran when Ukraine attacked. Ukraine now possesses positions on the high ground flanking Bakhmut, allowing it to be the one who shells Russia.

One of its top generals is now claiming that Ukraine is close to tactically encircling Bakhmut, basically meaning surrounding it on three sides. I don’t see evidence of that yet. But what interests me about the exaggeration is that it suggests Ukraine really wants Russia to send reinforcements to Bakhmut. It seems likely that in the near-term Ukraine will attempt to continue its gains on the high ground surrounding Bakhmut, drawing more Russians there to continue the battle of attrition, but this time with the terrain on its side. Because Bakhmut is its winter offensive’s big prize, Russia may be forced to commit troops there assaulting the high ground, diverting them from wherever Ukraine actually wants to attack.

And where might that be? I don’t know, but I do have a good target in mind.

Why Luhansk makes sense

Why attack Luhansk? Because, as Fredrick the Great would understand, that is what Russia has chosen not to defend. Unlike Kherson and Zaporizhzhia, it has only a single line of fortifications, behind the key city of Svatove, and it has no fallback positions behind it. The highways are empty. Many of its units there are still battered from Ukraine’s Kharkiv counteroffensive and winter fighting. The once-elite 1st Guards Tank Army on duty in Luhansk has been decimated twice now, first in Kyiv, then in Kharkiv.

If Ukraine punches through the single line of defense in Luhansk somewhere in the Svatove region, it’s hard to say what would stop it. It could potentially get all the way to the supply hub at Starobilsk pretty quickly, maybe even take it. Most of the northern half of Luhansk oblast would be at risk. It could swing south and surround Severodonetsk without dealing with the mass of fortifications there. There are a lot of options if Ukraine breaks through the single line around Svatove, manned by troops it’s already beaten and battered.

The approach I have in mind, breaching Russia’s defenses and then blitzing through northern Luhansk, would be an ideal task for Ukraine’s newly-armed elite 82nd Air Assault Brigade. Curiously, it has all 14 heavily armored Challenger 2 tanks, perfect for creating a breach, and all 90 fast Stryker APCs, perfect for exploiting one. It also has all 40 Marder IFVs—one interesting thing about the choice of the Marder rather than the Bradley is that the Marder is faster. The 82nd would be the perfect unit to spearhead a breakthrough of the front line and then run wild in Luhansk.

Russia has good reasons for not defending Luhansk as heavily as other places; it can’t defend everywhere equally, and the greatest risk is in the south. Northern Luhansk is no great strategic prize compared to Zaporizhzhia or Crimea, and lacks the symbolic importance Bakhmut has acquired. It’s also sparsely populated.

What northern Luhansk offers Ukraine is the chance for a relatively easy win early on, one that would offer a lot of territorial gain for a relatively minimal loss of lives. War is politics, this war more than most, and the scoreboard us idiot Americans look at to determine continued military aid cares more about quantity of territory acquired than the strategic value of it. We are not informed enough to care that Luhansk isn’t as valuable as Zaporizhzhia.

Besides, that territory does have value in a few ways. Operationally, Ukraine can move south to flank and surround fortified Donbas cities like Severodonetsk and Popasna. Politically, taking Luhansk has been one of Russia’s main goals from day 1 of the war. It would regret losing it. If Ukraine breaks through and runs rampant with relatively few fast mechanized brigades, Russia may panic and overcommit troops from elsewhere to stem the bleeding. That would open the door for Ukraine to reverse course using its shorter interior lines and launch a bigger attack elsewhere, somewhere it values more.

Maybe Ukraine will do something completely different. Probably it will. It has many options, along with the flexibility to switch course at any moment. In the end, Ukraine will likely attack wherever Russia has chosen not to defend.

Large companies like Microsoft have a major impact on their billions of users. But they also influence other companies’ cultures and policies, since former employees move on to other firms and use what they learned, and some people view things being done at large successful corporations as “best practices.” How these cultural and policy issues manifest themselves at universities has received a lot of attention. My aim in writing this piece is to raise awareness of what’s going on inside one of the world’s most valuable companies.

I’m publishing this article pseudonymously because I fear I would be fired or many companies would in the future refuse to hire me for writing it.

Microsoft classifies its employees by race, gender, and other categories, and aims to increase the shares of employees in preferred groups. This is not a secret. Microsoft has publicly committed to racial equity, including an effort to “double the number of US Black and African American, and Hispanic and Latinx people managers, senior individual contributors, and senior leaders.” The company publishes an annual report on Diversity & Inclusion (hereafter shortened to “D&I”) in which it tracks its progress toward such goals. Some “gains” noted in the 2021 report include:

• Amongst US employees, Hispanics increased from 6.5% to 7.0%.

• Amongst all employees, women increased from 28.6% to 29.7%.

• Amongst US executives, Blacks increased from 3.7% to 5.6%.

So how does Microsoft achieve this progress?

D&I Must be a Core Priority of Every Employee

Every Microsoft employee has to complete a “Connect” several times a year. As part of this process they must write out their priorities for the coming months, and how they plan to make progress on them (“critical indicators of success”). This text must be reviewed and approved by the employee’s manager.

You might think that a company that spent time writing a mission statement would ask employees to focus on its mission (Microsoft’s is “to empower every person and every organization on the planet to achieve more”). But every Microsoft employee instead is told that D&I must be a “core priority,” and that they should write about that first, and then “briefly” discuss their own additional priorities. Below is the text shown to employees:

When I initially saw this, I thought I would just write something anodyne and get back to focusing on producing great software for our users. But I soon learned that there was more to Microsoft’s commitment to D&I than making me write some text that was only visible to my manager every few months. I received an email from my corporate vice president (2 hops below the CEO), requiring all managers and employees above a certain level to publicly share our personal D&I plans.

I soon learned that if I wanted to get promoted, visibly announcing my commitment to D&I wasn’t enough. The corporate vice president who sent that email had to approve all promotions within his organization above a certain level, and it was made clear to me that he weighed contributions to D&I very heavily when making those decisions, and that he encouraged lower levels of management to do the same.

To contribute to D&I, people did and were encouraged to do the following:

• Hire “diverse” candidates (more on that below).

• Promote “diverse” employees (more on that below).

• Participate in a “culture club,” which organized speakers, book clubs, and movie showings focusing on topics like allyship and discrimination.

“Diverse” Candidates are Preferred During Hiring and Promotion

An important and challenging part of my job was hiring people at a time when the labor market was tight and our competitors were offering better compensation, remote work policies, and higher levels of prestige (would you rather work at Google on Gmail or at Microsoft on Outlook?). But in addition to all of these challenges, the company also put in place additional constraints in the service of D&I.

As a hiring manager, I was told that for any position to be filled in the United States I had to interview:

• At least 1 African-American, black, Hispanic, or Latin candidate, and

• At least 1 female candidate.

The slide below mentions a part of the company called “CELA” (Corporate, External, and Legal Affairs), but my impression was that it applied company-wide.

There weren’t any quotas around how many of these “diverse” candidates I had to actually hire, but I was pretty sure my corporate vice president would be more likely to promote people who had hired more of them and thus made his contribution to the annual D&I report look good.

For one position I was trying to fill, dozens of people applied, and most of them seemed qualified based on their resumes, but I spent months waiting for a single person to apply who fulfilled the racial requirement. When no one did, I spent hours trying to find people on LinkedIn who I thought might count as black or Hispanic based on their name or resume. Sadly, during these months I had many very qualified internal candidates applying for the role, but I couldn’t hire them. Unable to hire, my team became a bottleneck that delayed several projects integrating AI into Microsoft products.

You might imagine this policy doesn’t bias the hiring process, since managers are still free to choose who to hire after interviewing the diverse candidates. But because of the number of applicants, most are rejected based on their resumes. Imagine diversity candidates are 1% of the applicants but 15% of those interviewed. This gives those candidates opportunities to do well in interviews that their peers with similar resumes do not get.

In my role as a manager, I recommended employees for promotion. About a week after submitting one set of recommendations, I got an instant message from someone in human resources along the lines of “Hi, did you consider recommending [one of my subordinates] for promotion?” I replied, “I think I’m missing some context, can we discuss this over video?”

During the video call, I was told that HR was reviewing employees from “diverse” groups and making sure they had been considered for promotion. I told HR that I had considered it and I believed my recommendation was correct. HR said “OK, then we don’t need to change anything. I just wanted to check that you had considered them.”

Again, there was no quota, but it seemed clear that promoting this person would have made HR and my corporate vice president happy. At Microsoft, a division is given a fixed promotion budget each year, so promoting one person generally means not promoting another. 

Microsoft doesn’t discuss these policies with employees outside of HR and management. In the prompt that the company shows to all employees on its “core priority for diversity & inclusion,” the message is that D&I is about creating a culture “where we do our best work as a result,” and there is no mention of group identities or preferences in hiring and promotion. In this framing, D&I is a means of optimizing how people interact at work, not about changing the company’s demographics or giving better jobs to one group at the expense of another. In contrast, the hiring and promotion policies push away from hiring and rewarding people for contributing to the company’s mission. This is largely hidden from everyone other than managers and HR.

When I began my career, I believed that the systems for determining who got a job or a promotion at a company like Microsoft at least aimed at an ideal of meritocracy. Now I believe Microsoft hires and promotes people partly based on their group identities. Imagine you work under a black executive at Microsoft. Does a graph like this one make you more or less likely to think they got to where they are because of their accomplishments? 

I fear that when large companies hire and promote people based on group identities, it discourages individuals from cultivating their abilities and ultimately hurts the corporate mission.

In 1904, an Italian prince from a small township in Northern Italy lit five lightbulbs with power from a novel source: hot steam that leaked from the ground. His name was Prince Piero Ginori Conti. He had inherited his family’s boric acid business, which harvested and processed the chemical around hot springs in Larderello, near Florence. Around the turn of the century, Conti got curious about using the steam from the hot springs to generate electricity. And, after a few years of tinkering, he succeeded in a very small way.1

Geothermal energy, a term later developed to name what Conti discovered, has the potential to be a major player in the post-fossil fuel world. It’s carbon-free energy without the regulatory hurdles of nuclear, the intermittency of wind and solar, and the ecological damage of hydropower. But for geothermal to play a significant role in America’s quest for reliable, carbon-free electricity in the near future, we need to significantly alter the way we regulate companies seeking to produce geothermal energy.

We should exempt geothermal exploration on federally owned lands from the requirements of the National Environmental Protection Act, an exemption the government has already made for the oil and gas industry. The best thing would be for Congress to pass a law, but federal agencies could also make the exemption themselves. Making it easier for companies to look for the hot rocks they need to create utility grade power would set off a cascade of innovation by lowering the risks to forming new companies and experimenting with new technologies. With better policies surrounding geothermal exploration, the heat within the Earth itself could one day power millions of lightbulbs, and much more, all over America.

Geothermal energy takes a variety of forms, but the premise is simple. The inside of the Earth is staggeringly hot, and with the right technology in the right places, that heat can be used to power human activities. One estimate by Stanford's Global Climate and Energy Project suggests it exceeds the combined energy of every other stored energy source, like fossil fuels or uranium, 41 times.2 If we could capture all of it, we’d be able to power all of human civilization for hundreds of years.

Right now, all we can do is capture a fraction of the fraction that is closest to the surface in certain locations. In Iceland, 65% of primary energy, or energy harvested directly from natural resources, comes from geothermal.3 The island nation sits on a fault line, allowing magma from the Earth’s core to creep toward the surface. That warms water, which in certain places flows to the surface at high enough temperatures that it can be used to create electricity and heat buildings.

Most places aren’t like Iceland. In most places, all that heat is buried under too much rock and soil to access. But with new technologies, that could change. Instead of needing steam leaking from the crust, Enhanced Geothermal Systems (EGS) drill into the crust to reach hot rocks below.4 One pipe pumps water into the hole, where it gets hot, and another brings it back to the surface where it is converted into electricity. Other systems use fluids that heat faster and hotter than water, making it easier still to get those fluids to temperatures that can create electricity. Still others use closed loops to pump fluids into the rock, heat them, and then back up into the plant to create power.

There isn’t a clear line between traditional geothermal energy, like what’s used in Iceland, and EGS. The big difference is that EGS doesn’t need to be as close to a fault line or volcanic activity as traditional geothermal, opening up more places where it can be used. While much of this technology is promising, it’s still in its infancy. What these companies need is license to experiment, try new things, and improve their techniques.

But regulatory barriers stand in their way. One of the biggest is that geothermal companies must file environmental assessments under the National Environmental Protection Act (NEPA) to drill exploratory wells on federal lands. Companies can’t drill just anywhere and find hot enough rocks to create power plants. They must, like oil and gas companies, drill down to see what exists below the surface and whether or not it’s worth spending time and money to extract it. And, according to an analysis by the National Renewable Energy Laboratory (NREL), much of the land with geothermal potential in the United States is in the West, where the federal government manages a large portion of it.5

Having to file NEPA reports, which can run hundreds of pages and take years to review, only to see if the area has geothermal promise makes progress difficult and financing even harder. Ideally, companies would not be subject to lengthy NEPA processes until they have found a real resource and want to build a plant. Requiring NEPA filings for exploration significantly slows down an industry America needs to grow.

There’s a simple fix. The 2005 Energy Policy Act created a loophole for oil and gas exploration on federal land in Section 390 of the bill.6 If the exploration area is under five acres and the total site of the federal lands lease is under 150 acres, then the company doesn’t need to file the environmental assessment under NEPA rules. Almost all geothermal work fits that description. Congress should broaden this loophole, or what industry insiders call a “categorical exclusion,” to geothermal exploration. Another NREL analysis from 2019 estimated that doing so would increase the amount of discovered geothermal resources by 1% to 3% a year.7 NREL has also found that permitting under a categorical exclusion takes 88 days on average, while doing the full environmental assessment takes an average of 337 days.8

This rule change has accelerated development before. As Senior Researcher at the Utah State Center for Opportunity and Progress Eli Dourado has written, the categorical exclusion of oil and gas exploration for exploratory wells was a factor in creating the shale revolution.9 With greater freedom to explore and experiment, oil and gas companies discovered new ways to extract resources from rock formations previously thought to be impenetrable. Those advances led the U.S. to top the world in oil production and drove energy prices down everywhere. The same could happen with geothermal energy. And there is good reason to think this proposal could gather political support.

First, it's a small tweak in a law that would not gather huge amounts of attention. Such a change could be negotiated in “Secret Congress,” the term Matt Yglesias and Simon Bazelon have coined to describe where real work gets done on Capitol Hill.10 On issues that most people don’t think about and the media does not cover, Congress often passes substantial, practical legislation. For instance, in May 2021 Congress passed a $175 billion bill to upgrade America’s water and sewer infrastructure. At the end of 2020, it passed a $35 billion bill to invest in clean energy research and development. A lawmaker, likely from a Western state that would stand to benefit from geothermal expansion, could slip this into a larger energy or infrastructure bill.

Second, and unlike other types of renewable energy, exploring and developing geothermal energy requires many of the same skills as exploring and developing oil and gas. If geothermal energy was easier to permit and developed faster, large energy companies would have more incentive to pivot some resources away from fossil fuel drilling toward geothermal. Workers, too, could make the transition. This would soothe fossil fuel companies’ angst about their place in the future and possibly lessen their opposition to such a change. Indeed, there is a two year old conference called Pivot dedicated to exactly this: educate oil and gas companies on how they can shift to geothermal.11

Third, geothermal exploration doesn’t affect the environment. A 2014 NREL review of environmental assessments for 20 geothermal exploration wells found that every case resulted in a finding of no significant impact.12 This means exploration could expand faster while still preserving federal lands.

There are two ways geothermal exploration could get a categorical exclusion for exploration. As discussed above, Congress can create one through legislation, as it did for oil and gas exploration in 2005. The other is for federal agencies to examine certain actions and grant categorical exclusions to those that don’t have significant environmental impacts. This would involve taking a look at previous NEPA filings to see what impacts, if any, occurred, hearing from experts, and conducting demonstration projects to see what kind of impacts result.

The former approach is more likely, partly because there have been similar attempts in the past and legislation is brewing to try again. In 2011, Senators Mike Crapo (R-ID) and James Risch (R-ID) introduced a bill that would have granted geothermal exploration a similar categorical exclusion as the one for oil and gas. But it died in committee. In 2020, Senators Lisa Murkowski (R-AK) and Joe Manchin (D-WV) co-authored an energy bill that, among other things, would have excluded geothermal exploration wells from NEPA as long as they were under 2.5 acres. But that portion of the law was dropped when the larger energy bill was wrapped into a larger year-end spending bill.

However, with momentum building around support for carbon-free electricity and the geothermal industry growing larger, legislators might be open to changing these rules. The move would also unite classically Republican values of decreasing government regulation on business with classically Democratic values of promoting clean energy to fight climate change.

It could happen by introducing a new categorical exclusion for geothermal, as Crapo and Risch attempted in 2011. In fact, Risch has teamed up with Idaho Congressman Russ Fulcher (R-ID) to introduce a bill that would provide a categorical exemption to geothermal exploration that mirrors the one for oil and gas.13 But its status is unclear, and it could die in committee just as it did in 2011. As Congress considers doling out billions in clean energy tax credits through the Build Back Better Act, or whatever legislation takes its place, surely it would also want to find ways to make those dollars go further. Including the Risch-Fulcher Act in that bill would mean more clean energy would flow into the American power system.

To see the value geothermal energy can create, consider where it all began. After successfully powering his five lightbulbs in 1904 with geothermal energy, Conti thought bigger. In 1913, he helped open the world’s first geothermal power plant, Larderello 1. It’s still in operation today and has been expanded to 34 plants that provide 800 megawatts of clean, carbon-free electricity to the towns nearby. One day, power plants like it could dot America, providing clean energy at all hours of the day. To get there, we need regulatory reform.

Andrew Kenneson works for a public housing authority in Kodiak, Alaska. Before that, he was a reporter at local newspapers in Kodiak and in Monroe, Georgia. His email is akenneson21@gmail.com.

Subscribe now

Read the other prize-winning essays from the CSPI Essay Contest:

• “Mo’ Money Mo’ Problems” by Maxwell Tabarrok

• “Drone Airspace: A New Global Asset Class” by Brent Skorup

• “The University-Government Complex” by William L. Krayer

• “It’s Time to Review the Institutional Review Boards” by Willy Chertman

This essay won second prize in the CSPI Essay Contest: Policy Reform for Progress.

Science, broadly defined as understanding and control of the natural world, is at the foundation of every step humanity has taken from hunter-gatherer to post-industrial knowledge worker. If we hope to take further steps into a new future, whether it be planet-faring space colonization, solar-punk communalism, or crypto-capitalist globalization, more science will be needed.

The importance of science to civilizational progress makes the organization of its production of paramount importance. Our current method of buttressing market production with state subsidies nominally contributes hundreds of billions towards science, but it produces turbulent second-order effects and strategic adaptations which dissipate most, if not all, of the nominal gains. Therefore, increasing tax dollars for science without changing the channels through which it flows will not be sufficient to bring the production of truly impactful science up to socially optimal levels.

Context

Government funding of science, especially at the massive scales seen today, is a recent phenomenon tracing back to WWII. Before 1940, over 90% of research and development was funded privately. Today, industry outspends government on research and development almost 3 to 1.

Still, the logic behind state support of science is strong. Scientific ideas have positive impacts that researchers are not rewarded for. The best scientific ideas are important long after the death of their creator. They are spread around the world and inspire many subsequent advances. William Nordhaus estimated that less than 2% of the gains in human welfare from scientific advances are actually captured by the creator. These positive externalities imply underproduction of the most important input into civilizational progress, making science a prime target for subsidy.

Acknowledging that science and technology are underrewarded by markets is easy but figuring out the best way to correct this is more difficult. In total, the federal government spends around $120 billion dollars on science and its applications. Most of this money is distributed through grants to researchers and universities. About half of these funds are spent by the Department of Defense (DoD), and most of the other half goes through the National Institutes of Health (NIH) and the National Science Foundation (NSF).

While this government support has significantly increased the number of PhD researchers and the volume of published papers, the outputs of scientific progress that we care about no longer seem to be tracking with these metrics. Half of all scientific papers ever published were published in the last 12 years, but it is clear that much less than half of all scientific progress occurred in that time. The number of published papers, citations, and patents are becoming decoupled from total factor productivity growth, per capita energy use, travel speeds, and construction costs.

The Problems

Rent Dissipation

The first problem with our current methods for funding science and technology is called rent dissipation. When we say that “the federal government spends $120 billion on science” we have to subtract from that sum the value of all the time and resources that were spent courting that transfer of tax dollars. This idea was first developed by economist Gordon Tullock in a study of protected monopolies. Take, for example, a cable company that is given a monopoly on TV services. Econ 101 analyzes the situation with a graph:

Monopolies are inefficient so there is some pure loss of resources to society, represented by the green triangle. The monopoly can charge a higher price than normal from their customers, so they make extra profit, represented by the pink rectangle. This money is just transferred from consumers to the monopolist, so it’s not deadweight loss. As Tullock says, “We may object to the monopolist getting rich at the expense of the rest of us, but it is not a decrease in the national product.”

However, Tullock knew that these government transfers are not random – they are bought, sold, and produced by lobbying and political influence. If the monopoly contract gives our cable company 2 million dollars in extra profit, then they can spend $1,900,000 on lawyers and political campaigning and still make a profit, although they produce nothing for society. This spending on rent-seeking is deadweight loss and it dissipates the positive effect of the transfer.

A similar story can be told with state funding of scientific research. Government transfers wealth to researchers, but they only get what the government gives them minus what they spent acquiring the funding. What are the costs of getting scientific funding from the state? They include completing application forms and writing grant proposals, changing your research agenda to fit the state’s goals, and waiting weeks, months, or years for revisions and decisions. These costs are not insignificant. A survey done by Fast Grants of the hundreds of scientists that they have funded over the past few years reveals that:

• 32% said that Fast Grants accelerated their work by “a few months.”

• 64% of respondents told us that the work in question would not have happened without receiving a Fast Grant.

• 57% of respondents told us that they spend more than one quarter of their time on grant applications.

• 78% said that they would change their research program “a lot” if their existing funding could be spent in an unconstrained fashion.

• 81% percent of those who responded said their research programs would become more ambitious if they had such flexible funding.

• 62% said that they would pursue work outside of their standard field (which the NIH explicitly discourages).

• 44% said that they would pursue more hypotheses that others see as unlikely.

A scientist who benefits from a 2-million-dollar NIH grant is willing to spend a million dollars of their time working on applications or incur the cost of restricting their research ideas in order to get it. Importantly, even though only one scientist will get the grant, hundreds of scientists are spending resources in competition to get it. So the gains we might be seeing from transferring resources to one researcher are dissipated multiplicatively across all the scientists who spent time and money competing for the grant but didn’t get it. The aggregate time costs to our brightest minds from this application contest system are quantifiably large, possibly entirely offsetting the total scientific value of the research that the funding supports. The costs of restricted research agendas, while much harder to measure, are plausibly even larger. As the ratio of applicants compared to awardees continues to grow, more researchers' time is wasted for the same benefits.

Risk Aversion

The second countervailing effect of state-funded science is the risk aversion inherent in the consensus-based bureaucracy that runs our government and universities. Exemplifying this is the NIH’s council of councils that administrates their numerous sub-councils and committees. Successful NIH grant applications are typically reviewed by 10-20 scientists and program officers across three phases of review over months to years. In some sense this is good, since attestation from qualified colleagues is obviously good evidence for the quality of an idea. However, our current system is only one of many different ways of measuring and integrating this evidence, and it comes with some serious drawbacks.

In our current science funding vetocracy, only ideas that few or no established scientists object to will be funded and rewarded. Naive credentialism sees this as a good thing, but hindsight shows that many of the most transformative discoveries we take for granted today were objected to by the most prestigious scientists and experts of their time.

• 1878: “When the Paris Exhibition closes, electric light will close with it and no more will be heard of it.” – Oxford professor Erasmus Wilson.

• 1889: “Fooling around with alternating current is just a waste of time.  Nobody will use it, ever.” – Thomas Edison

• 1895: “Heavier-than-air flying machines are impossible.” – Lord Kelvin, British mathematician and physicist, president of the British Royal Society.

• 1913: “Lee DeForest has said that it would be possible to transmit the human voice across the Atlantic before many years. Based on these absurd and deliberately misleading statements, the misguided public ... has been persuaded to purchase stock in his company ...” – a U.S. District Attorney, prosecuting American inventor Lee DeForest for selling stock through the mail for his Radio Telephone Company.

• 1932: “There is not the slightest indication that nuclear energy will ever be obtainable. It would mean that the atom would have to be shattered at will.” – Albert Einstein.

• 1939: “Look, you should stop the work you are doing. It isn’t going to work. You know it’s not going to work. We know it’s not going to work. You’re wasting money. Just stop!” – Nobel Laureates Isidor Rabi and Polykarp Kusch to future Nobel Laureate Charles Townes about his work on the laser.

• 1946: “Television won't be able to hold on to any market it captures after the first six months. People will soon get tired of staring at a plywood box every night.” – Darryl Zanuck, 20th Century Fox.

• 1961: “There is practically no chance communications space satellites will be used to provide better telephone, telegraph, television or radio service inside the United States.” – T.A.M. Craven, Federal Communications Commission (FCC) commissioner.

Sitting on present-day review boards, any one of these highly qualified commentators would have vetoed funding and publication for these projects which, in hindsight, we know were all huge successes. This past perspective should illuminate the lost potential of present-day projects which are shut down by a confident veto on a peer review committee. More recent examples include promising research paths to a cure for Alzheimer’s being shut down and Katalin Karikó, a principal researcher behind mRNA vaccines, being denied funding and demoted from her position at the University of Pennsylvania. In aggregate, this bias towards consensus has led to huge investments in paradigm-confirming incremental papers that are likely to garner citations, but unlikely to make impactful advancements in our understanding. This has resulted in ossification of the most influential papers in a field rather than the turnover characteristic of a field correcting and improving itself, and underinvestment in young scientists who are most likely to make paradigm-shifting discoveries.

The Proposal: Researcher Guided Funding

The problems outlined above are not insurmountable. With significant reforms, government funding of science could promote the production of positive externalities without creating undermining incentives. What would these reforms look like, and how would they improve on market outcomes?

To avoid rent dissipation and risk aversion, our state funding of science should be simplified and decentralized into Researcher Guided Funding. Researcher Guided Funding would take the ~$120 billion spent by the federal government on science each year and distribute it equally to the ~250,000 full-time research and teaching faculty in STEM fields at high research activity universities, who already get 90% of this money. This amounts to about $500,000 for each researcher every year. You could increase the amount allocated to some researchers while still avoiding dissipating resources on applications by allocating larger grants in a lottery that only some of them win each year. 60% of this money can be spent pursuing any project they want, with no requirements for peer consensus or approval. With no strings attached, Katalin Karikó and Charles Townes could use these funds to pursue their world-changing ideas despite doubt and disapproval from their colleagues. The other 40% would have to be spent funding projects of their peers. This allows important projects to gain a lot of extra funding if a group of researchers are excited about it. With over 5,000 authors on the paper chronicling the discovery of the Higgs Boson particle in the Hadron Supercollider, this group of physicists could muster $2.5 billion dollars a year in funding without consulting any outside sources. This system would avoid the negative effects of long and expensive review processes, because the state hands out the money with very few strings, and risk aversion among funders, because the researchers individually get to decide what to fund and pursue.

This idea is not fully fleshed out and there are some immediate problems that arise. An equal distribution of funding among all STEM researchers is a poor first approximation since some researchers are much more impactful than others, although the fungible 40% would flow mostly towards top talent. Additionally, since this distribution is defined via somewhat arbitrary classifications of universities, there would be discontinuities at the boundaries between STEM and non-STEM fields and high vs. not high research activity universities. Large sums of money would become available to universities and fields that managed to change their classification, so there would be a surge of claimants who would dilute funding from our most important researchers.

The True Proposal: Experimentation

The unsolved issues with this proposal lead me to the true proposal for reforming government funding of science: a government that rapidly experiments with many different strategies. Not all that many ways of funding science have been tried, so no one has strong evidence that their preferred system will work. What we do know is that our current system is falling short. A truly enlightened state would use the same scientific method it is funding to analyze and improve its own efforts over time.

With the current $120 billion that the federal government spends on science and technology, we could create 10 focused research organizations for different scientific and technological goals in artificial intelligence, bio-engineering, advanced transportation, and energy tech – each with a $10 billion dollar budget and unique management strategy. We would still have $10 billion dollars left to fund 100 hundred-million-dollar prizes for achievements in a wide range of fields, and $5 billion more to distribute annually in 5 thousand Macarthur-style genius grants to the nation’s top minds to be put towards any project they wish. The final $5 billion would be used to fund a meta-study of the impacts and efficiencies of each of these strategies. The allocations between each of these strategies or new funding methods can be randomly tweaked to provide exogenous variation necessary to study the causal effects of marginal increases in funding between each of these strategies. As we gather more data over time, we can decide to change the permanent allocations of funding between strategies or introduce new funding methods that we want to test.

Conclusion

Government funding of science is a logical and well-intentioned attempt to increase the production of a positive externality. However, the institutional forms in which we have chosen to distribute these funds have created parasitic drag on the progress of science. There are many exciting proposals for new ways to fund science, but picking any one of these without rigorous experimentation would be foolish and ironic. The best proposal for science funding reform is to apply science to the problem. Rapid and large-scale experimentation is needed to continuously update and improve our science funding methods.

Maxwell Tabarrok is an Econ and Math student at the University of Virginia. He blogs at maximumprogress.substack.com. Follow him on Twitter @MTabarrok.

Subscribe now

Read the other prize-winning essays from the CSPI Essay Contest:

• “Gathering Steam: Unlocking Geothermal Potential in the United States” by Andrew Kenneson

• “Drone Airspace: A New Global Asset Class” by Brent Skorup

• “The University-Government Complex” by William L. Krayer

• “It’s Time to Review the Institutional Review Boards” by Willy Chertman

This essay won third prize in the CSPI Essay Contest: Policy Reform for Progress.

Background

The first mobile telephone service, linking moving cars, debuted in the United States in 1946. However, the technology languished for decades globally as national regulators dribbled out spectrum to inert industry supplicants via multi-year rationing proceedings.

In 1980, McKinsey & Co. advised AT&T, their client, that US mobile phone subscriptions in 2000 would top out at less than 1 million. Two years later, in 1982, with company breakup imminent, AT&T executives volunteered to federal antitrust officials to forfeit their minuscule, money-losing mobile phone business. Unfortunately for AT&T shareholders, McKinsey analysts were off by two orders of magnitude – there were more than 100 million mobile phone subscribers in 2000. In AT&T’s and McKinsey’s defense, they didn’t anticipate two intervening spectrum policy innovations: government auctions and flexible-use rules.

Government spectrum sales and liberal technology rules were first proposed in 1951 by law student Leo Herzel1 as a technique to allow the development of competing radio technologies. The provocative idea faced rejection by DC telecommunications experts and industry, including an immediate law review rebuttal by a former FCC chief economist. In 1962, the RAND Corporation commissioned a spectrum policy paper from prominent economist Ronald Coase. His recommendation of government spectrum sales, an idea drawn from Herzel’s paper, was fiercely criticized by RAND’s internal reviewers for ignoring FCC expertise in technology selection. Coase’s draft submission to RAND was considered so explosive and damaging to RAND’s reputation if published that they suppressed the report.2

However, spectrum in the late-1980s was appreciating in value, and administrative assignment of spectrum was increasingly contested. A handful of heterodox FCC economists had begun operationalizing the spectrum markets idea and convinced Congress to authorize spectrum auctions in 1993. Other countries followed suit and cellular phones rapidly went from an expensive curiosity to a life-changing and ubiquitous service.

Today, there’s a similar gold rush for a new global asset class – drone corridors and low-altitude airspace. Policymakers must adopt airspace markets, lest drone services become ossified by regulation like wireless services pre-1993. Private investment is pouring into the commercial drone industry, including small drones as well as large, electric cargo drones and passenger drones. Drone airspace resembles spectrum in the 1980s, an appreciating asset that could be bought, subleased, traded, and borrowed against – if it were only permitted.

Much like legacy spectrum policy, there is immense technocratic inertia towards rationing airspace use to a few lucky drone companies. The Federal Aviation Administration (FAA) has begun drafting long-distance drone rules for services like home delivery, business-to-business delivery, and surveying. In the next decade, drone services companies will deploy mass-market parcel delivery and medical deliveries in urban and suburban areas to make deliveries and logistics faster, cheaper, and greener.

There’s no congestion today, but regulators have yet to identify methods to manage airspace in anticipation of millions of small and large drones contending for high-traffic routes and for landing. Linear networks – whether air travel, railroads, roadways, or the Internet – cluster into a hierarchy of congested nodes and face lumpy traffic peaks. Drone routes will too. Federal officials recognize that the current centralized system of air traffic management won’t work for drones: at peak times today, US air traffic controllers actively manage only about 5,400 en route aircraft.

Red flags abound, however. FAA’s current plans for drone traffic management, while vague and preliminary, are clear about what happens once local congestion occurs: the agency will step in to ration airspace and routes how it sees fit. Further, the agency says it will closely oversee the development of airspace management technologies. This is a recipe for technology lock-in and intractable regulatory battles.

US aviation history offers the alarming precedent of expert planning for a new industry. In 1930 President Hoover’s Postmaster General, who regulated airmail routes, and a handpicked group of business executives teamed up to “rationalize” the nascent airline marketplace. In private meetings, they eliminated the established practice of competitive bidding for air routes, divided routes amongst themselves, and reduced the number of startup airlines from around forty to three.

“Universal” and “interoperable” air traffic management are popular concepts in the drone industry, but these principles have destroyed innovation and efficiency in traditional airspace management. The costly US air traffic management system still relies on voice communications and manual writing and passing of paper slips. Large, legacy users and vendors dominate upgrade efforts, and “update by consensus” means the injection of innumerable veto points. Drone traffic management will be “clean sheet,” but interoperable systems are incredibly difficult to build and, once built, to upgrade with new technology and processes. More than 16,000 FAA employees worked on the over-budget, pared-down, years-delayed air traffic management upgrades for traditional aviation.

Airspace Markets Proposal

It’s often only in hindsight that we see that technocrats and their industry dependents cloaked anticompetitive market division and stifling government micromanagement with pretend expertise, insider-dominated stakeholderism, and volumes of startup-destroying rulemaking deliberations. As the AT&T and McKinsey episode reveals, even the financially interested participants don’t see what’s happening. There’s still time to protect competition and innovation in drone services and technology. To avoid anticompetitive “route-squatting” and sclerotic bureaucratic control of a new industry, aviation regulators should announce a national policy of “airspace markets” – government sales of high-demand drone routes, resembling present-day government spectrum auctions.

With airspace markets, winning bidders win the exclusive license to manage, combine, and sublease air corridors. Importantly, operators have the freedom to iterate and to use the drone traffic management systems and technologies of their choice (subject to generally applicable FAA safety rules like separation minimums and emergency procedures). This freedom to upgrade without competitor or vendor approval is absent in traditional aviation but necessary in a fast-moving sector like drone wireless and sensing technology. While relinquishing control is painful, officials benefit by turning a regulatory cost center into a profit center. The US and state governments will receive regular, passive revenue from commercial use of this new asset class – aerial corridors.

This airspace markets proposal has circulated at publications ranging from the Marginal Revolution blog, drone trade press, Government Accountability Office reports, and an Airbus white paper. However, like spectrum sales, the idea of airspace markets has met visceral opposition in Washington. Four states attempted to codify the airspace markets proposal in 2021, but each bill was defeated by opposition from a handful of drone companies.

The idea is circulating, however, and some in industry have welcomed it, including a former FAA Chief Counsel. It’s only a matter of time before parties outside of DC aviation circles notice the commercial prospects of airspace markets. In the next few years, as drone delivery programs expand, linear property owners and rights-of-way managers – railroads, telecoms, utility companies, municipalities, and REITs – will wake up to the possibility of generating passive income from their currently unused air rights.

Next Steps

When that happens, federal and state aviation authorities will be under immense pressure to prevent route markets for drones. Fortunately, current state laws tolerate and sometimes even encourage low-altitude (sub-200 feet) airspace sales to commercial users. At the higher altitudes where cargo and passenger drones will transit, the FAA’s authority is broad and allows for airspace markets. The agency has statutory authority to “assign the use of the navigable airspace under such terms, conditions, and limitations as [the agency] may deem necessary in order to ensure the safety of aircraft and the efficient utilization of such airspace.”3 The FAA can lease “any interest in property,” including airspace, for “adequate compensation,”4 and the Secretary of Transportation is instructed by statute to “plac[e] maximum reliance on competitive market forces.”5 These state and federal laws have never before been contemplated for drone and aviation services, however. Therefore,

1. For low-altitude (sub-200 feet) airspace, the USDOT and FAA should announce a policy endorsing the ability of linear property owners to lease airspace to drone and property investors. This would almost immediately summon 8 million miles of drone corridors into existence above roadways, plus millions more miles above railroad and utility rights-of-way.

2. For the higher-altitude routes that the FAA controls, the agency should begin designating cargo and passenger drone routes – central business district to airport corridors will be in high demand – and announce a policy of competitive bidding when there are more interested parties than corridors.

3. In anticipation of competitive bidding, the FAA should form an interagency task force with the Federal Communications Commission to advise on auction and lease of government assets. The FCC’s spectrum team has conducted dozens of auctions yielding hundreds of billions of dollars of revenue.

The current government proposals, shared and regulated airspace and infrastructure access, makes investments precarious. In contrast, exclusive corridors give licensees stability of possession that induces the significant infrastructure investment necessary for mass-market drone delivery, sensor, and logistics systems. This is the model that drives tens of billions of capex investment into US wireless systems, which recently upgraded to 5th-generation (5G) services.

It took over 40 years for Leo Herzel’s thought experiment about spectrum sales to become the global standard for government spectrum disposition. Before it was an inevitability, the idea was mocked by FCC staff, suppressed by the RAND Corporation, and ignored (at great expense) by AT&T and McKinsey & Co. Airspace, like spectrum, is an intangible global asset class. It should take less than four decades for regulators and industry to see the possibilities of airspace markets.

Brent Skorup is a senior research fellow at George Mason University's Mercatus Center and a visiting faculty fellow at the Nebraska Governance and Technology Center at the Nebraska College of Law. Follow him on Twitter @bskorup.

Subscribe now

Read the other prize-winning essays from the CSPI Essay Contest:

• “Gathering Steam: Unlocking Geothermal Potential in the United States” by Andrew Kenneson

• “Mo’ Money Mo’ Problems” by Maxwell Tabarrok

• “The University-Government Complex” by William L. Krayer

• “It’s Time to Review the Institutional Review Boards” by Willy Chertman

In the CSPI Essay Contest: Policy Reform for Progress, this essay won an honorable mention.

This essay will propose certain reforms Congress can undertake to revive the innovative and entrepreneurial spirit that propelled the economy to outstanding prosperity in the past.

Economist Tyler Cowen has declared that the extraordinary explosion of innovation in the United States in the period roughly from 1850 to 1970 was a fluke in human history, at least partly because such fundamental technologies as railroads and electric power arrived at a time when America had lots of free land and a rapidly growing population. He called the practical inventions that propelled American prosperity “low-hanging fruit.” There are good reasons to question this analogy, but the data clearly show differences between the two periods.

This essay posits that the return to lackluster improvements in productivity beginning around 1970 was not a return to normalcy but traceable to several factors that require remedies on the federal level.

Economists measure the effects of innovation and entrepreneurship in terms of productivity increases and as part of Total Factor Productivity (TFP), which includes the effects of investment in new technology. These measures show significantly reduced rates of increase in recent decades – that is, at the same time government research funding increased significantly. This does not prove an etiological relationship, but there are other correlations to be discussed below.

Background

In a review of university research, Michael S. Teitelbaum observed that the present predominantly federally funded system evolved from a mainly fellowship funded model.1 In 1944, the eminent scientist Vannevar Bush wrote a report titled “Science: the Endless Frontier,” recommending the establishment of a “National Research Foundation,” which would financially support students and universities rather than wholly government-owned research laboratories. The idea was embraced but has evolved into a system of greatly increased funding of research to serve a vision of sustainability rather than productivity enhancement.

Teitelbaum’s book is mainly about the boom and bust history of employment for scientists and engineers, but also pointedly says “US research universities are widely admired around the world for their high level of research productivity” and “On balance, it is fair to say that the US system has been a triumph of major proportions.”2

This is the almost universal opinion in academia, buttressed by statistics on the numbers of startup companies founded with grant-supported research, numbers of patents, stories about “basic” breakthroughs and exotic technologies, groundbreaking papers, and so forth. In their embrace of research, American universities are far from the “comatose” state noted by the eminent British historian Paul Johnson, referring to British universities during Britain’s famous industrial revolution.3 Research in American universities is booming because of federal subsidies, but the economy does not seem to notice. University research has little or no effect on the economy because it is directed by elites who are out of touch with the needs and desires of the marketplace.

In Dwight D. Eisenhower’s presidential “Farewell Address” on January 17, 1961, he famously warned of the “military-industrial complex.” Not as well remembered has been his admonition that “The free university, historically the fountainhead of free ideas and scientific discovery, has experienced a revolution in the conduct of research. Because of the huge costs involved, a government contract becomes virtually a substitute for intellectual curiosity.” The “domination of the nation’s scholars” by the power of federal money was a danger “to be gravely regarded,” as was the danger that “public policy could itself become the captive of a scientific-technological elite.”4

More than sixty years later, it is time to look again at the relationship between the universities and the federal government, which has become what I call the “University-Government Complex.”

The University-Government Complex

Around 1970, federal funding of research at universities began to increase noticeably, and further accelerated after the passage of the Bayh-Dole Act of 1980. The National Science Foundation was not the only source of funding – the NIH, and cabinet departments such as the Departments of Energy and Defense, also greatly increased funding. Federal money dominates, and an elite class dictates the course of research. 

President Eisenhower was ignored. But consider the following more recent comments from Nobelist Edmund Phelps:

In the medieval past, (it was) supposed, attempts to innovate were directed by the economy’s communal authority, with results generally along the lines of what the community had hoped. When such communal goals came to be largely crowded out by the unannounced, largely unobserved, and often inscrutable initiatives of a welter of individuals and companies in the business sector, the economy could be said to have been left rudderless, which gave rise, understandably enough, to a sense of disorder. And that sense, no doubt, lay behind some of the unease felt across Western Europe in the last years of the 19th century and the early decades of the 20th. The desire for direction (for dirigisme, as the French said), was a major strand of corporatist thought.

This is the doctrine dubbed techno-nationalism by Richard Nelson. It is one manifestation of the more general belief called scientism – the belief that scientists, equipped with the tools of their science, more effectively advance the flowering of new products and methods than do the diffuse and poorly directed initiatives taken in a free enterprise economy. It was under Mussolini in 1923, then prime minister, that Italy founded its Consiglio Nazionale della Ricerche, a full 27 years before America’s National Science Foundation.5

The nationalistic Mussolini-imitating visionaries, who supply the dirigisme of American university research, are not good for the economy.

Prior to the enactment of Bayh-Dole, government-funded research at universities was notoriously unutilized in commerce, primarily because of a policy that profit-seeking entities should not benefit from publicly funded research. Therefore, the reasoning went, even if an invention was patented, anyone could use it; no entity could have exclusive rights. The new Act sensibly recognized that no one wanted to invest in an untried idea if it could be immediately copied, and that there should be a way for government-funded inventions to be commercialized so that their benefits could be seen in the public sphere. 

Under the Bayh-Dole Act, typically, a professor known as the Principal Investigator (PI) is appointed by a university to undertake a research project funded by the government. Often using equipment paid for by the grant, and with free graduate student help, he invents something and the university patents it. Being a “non-profit” entity,6 the university cannot commercialize the idea, so the professor forms a company – a startup – and the university grants it an exclusive license that requires royalty payments to the university. The royalty income, highly profitable by any accounting standard, is by law not taxable to the university. The university is, however, required to share perhaps 30% of the royalty with the inventor(s). So the professor collects his royalty share as well as the stock options and salary typical of the usual startup company. The contrast with the risks taken by the traditional entrepreneur-inventor is stark.

What Are We Funding?

Government entities such as the NIH and the Department of Energy have goals relating to their fields and solicit applications for grants accordingly. In recent decades, the Department of Energy’s choices have been driven by climate warming convictions bordering on hysteria. Many NSF subjects are also climate or environmentally oriented, often attempting to influence drastic changes in energy usage.7

But after noting, among other eyeopeners, that “Greenland’s ice sheet isn’t shrinking any more rapidly today than it was eighty years ago,” Steven E. Koonin, former Undersecretary for Science in President Obama’s Energy Department and ranking member of various international committees on climate change, wrote:

The earth has warmed during the past century, partly because of natural phenomena and partly in response to growing human influences. These human influences (most importantly the accumulation of CO2 from burning fossil fuels) exert a physically small effect on the complex climate systems. Unfortunately our limited observations are insufficient to usefully quantify either how the climate will respond to human influences or how it varies naturally. However, even as human influences have increased almost fivefold since 1950 and the globe has warmed modestly, most severe weather phenomena remain within past variability. Projections of future climate and weather events rely on models demonstratively unfit for the purpose.8

In his book, Dr. Koonin deplores the hyperbolic and apocalyptic predictions not only in the popular media, but especially from governments and scientific sources.

Scientists from academia are tapped for positions in the NSF, where they write solicitations for projects doling out billions to their ideological colleagues. This article cannot begin to document the hundreds or thousands of recent grant proposals and requests that seem like parodies or satires, such as the one partly reproduced in this footnote9 listing the “grand challenges” of the überclever homonymic acronym INFEWS (Innovations at the Nexus of Food, Energy and Water Systems) that must be met. One writing a grant proposal in response will be careful to use the reverent upper-case E for “earth,” and to stifle the urge to hint at future renewals of the grant when it becomes undeniable that the quest for “sustainability” is never-ending. At the same time, a commonsense engineer in a regional sanitary authority, simply trying to find a site for a new sewage plant, can only wonder if the world has gone mad.

There is a closely followed “success rate” for research grants – not necessarily for the research, but for obtaining grants. The success rate has declined by 50% recently because competition among research universities has accelerated. Some schools have graduate courses in grant writing. Experience in the granting agencies of government is a plus for applicants for positions in universities. Patent attorneys and technology transfer specialists proliferate in the universities, such that patenting occurs at a rate per research dollar far above that of private industry. But inventories of unlicensed patents pile up because many of the patents are on inventions that no one wants. Rent-seeking and public choice principles are on vivid display throughout the University-Government Complex.

Too much of America’s fortune and talent are squandered on useless effort.

Here is What Congress Could Do:

1. Abolish the National Science Foundation. It has not increased productivity in the economy. Its attempts to advance so-called renewable energy seldom take the kinds of practical approaches private industry would; they lead to never-ending public subsidies, a major drag on the economy. Its abuse is beyond redemption.

2. Drastically reduce research expenditures in cabinet departments on energy research. Trust that traditional incentives will encourage private investment in what the public wants and needs. Oversight could be strengthened for specific entities such as NASA.

3. Recognize that universities are profit-making. “Stakeholders” such as administrators and professors benefit financially. Revise the tax laws accordingly.

What Then?

Follow the advice sometimes attributed to that great contemporary philosopher Clint Eastwood: “Don’t just do something – stand there!” And watch the market work – again.

William L. Krayer is a semi-retired intellectual property lawyer and past president of the Pittsburgh Intellectual Property Law Association.

Subscribe now

Read the other prize-winning essays from the CSPI Essay Contest:

• “Gathering Steam: Unlocking Geothermal Potential in the United States” by Andrew Kenneson

• “Mo’ Money Mo’ Problems” by Maxwell Tabarrok

• “Drone Airspace: A New Global Asset Class” by Brent Skorup

• “It’s Time to Review the Institutional Review Boards” by Willy Chertman

In the CSPI Essay Contest: Policy Reform for Progress, this essay won an honorable mention.

Institutional Review Boards (IRBs) are ethics committees, ideally composed of scientific peers and lay community members, that review research before it can be conducted. Their ostensible purpose is to protect research subjects from research harms. But oftentimes, IRBs are costly, slow, and do more harm than good. They censor controversial research, invent harms where none exist, and by designating certain categories of subjects as “vulnerable,” cause a corresponding diminishment in research on those subjects. There is even a plausible legal argument that they violate researchers’ First Amendment rights. Because previous attempts to spur the responsible federal executive agencies into streamlining IRBs have been unsuccessful or only had limited success, a targeted legislative solution that does not depend on bureaucratic implementation is needed. 

How Did We Get Here?

The IRB system is a useful case study on how well-intentioned government oversight can, over time, develop into a pseudo-morality, complete with a secret decision process, a designated priestly class of “IRB administrators” who study a holy text (the Belmont Report),1 and laypeople invoking heresy.

Starting in the 1940s, various professional organizations developed codes of research ethics, though none had the force of law or had reached a consensus. Precursors to IRBs have existed in large scientific institutions like the NIH since the early 20th century but emerged on a large scale in the 1960s and 70s, with the Public Health Service instituting an overview process of medical and psychological research grants in 1966.

In response to highly publicized biomedical research scandals, most notably the Tuskegee Experiment, Congress passed the National Research Act of 1974. This created the National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research, which published the Belmont Report in 1976. As historian Zachary Schrag has amply documented in Ethical Imperialism, the commission was sorely lacking in social science expertise from the beginning. This was logical, since the most egregious research scandals, like the ones documented in this landmark 1966 Beecher article, were the work of biomedical researchers.2 

The federal government initially shied away from heavy-handed oversight of the social sciences, who had a powerful champion for academic freedom in Ithiel de Sola Pool. However, a gradual scope-creep, spearheaded by successive leadership of the Office for Human Research Protections (OHRP) in the Department of Health and Human Services, ensured that by the early 1990s practically all social science research involving human subjects had to undergo IRB review. 

Questionable Legality

This “ethical imperialism” was accomplished through murky legal means. First, the federal government required institutions that accepted any research funding to certify that all research (including non-government funded research) would undergo IRB review. Second, to bypass the mandatory public comment period that accompanies administrative rulemaking, OHRP issued “suggested” guidance that was practically never disobeyed. Third, when explicitly instructed to reduce research regulations by the incoming Reagan administration, OHRP issued stricter rules instead.

Accompanying the top-down regime was a growing class of IRB professionals, a far cry from the academic peers that were originally envisioned to review research proposals. This class of compliance professionals has constituted itself in trade associations like the PRIM&R and AAHRPP, and now serve a quasi-private role in interpreting the vague pronouncements of OHRP for their captive university and industry consumers.

Questionable Necessity

However unglamorous the origin of IRBs, the more damning fact is that IRBs are, mostly, a ham-fisted “solution” to a trumped-up problem. As Schneider argues at length in The Censor’s Hand:

[Being a subject] is not particularly hazardous...surveys both before and after the rise of the IRB system found few examples of serious risk3...people and institutions with incentives to discover and publicize risk locate little...studies repeatedly find that patients are not hurt and might be helped by being research subjects.

In the social sciences, the basis for IRB review is even weaker. Per Schrag’s Ethical Imperialism, Congress never intended to regulate social science. In fact, the studies cited as justification for research oversight in the Belmont Report are biomedical research. Decades later, in an interview with historian Zachary Schrag, two members (Jonsen and Beauchamp) of the original commission that wrote the report effectively admitted that the regulation of social science research by the same methods as biomedical research was a mistake.

As justification for their continued existence, IRBs have cited increasingly non-physical “harms” to subjects with little empirical support. For example, IRBs sometimes view speaking with trauma survivors about their trauma as a presumptively harmful act. This is likely incorrect, and avoiding those topics only delays squarely addressing them. A more concerning systemic problem with IRBs is their role as institutional censors. Some IRBs have explicitly stated that certain subjects, because of their controversy, face stricter scrutiny. IRBs also fear a media outcry, and limit local researchers as a result. Over several decades of social science research, it is not clear if any subject deaths have ever occurred as a result.

On the other hand, conservative estimates of deaths that IRBs have caused through delays to research trials are in the several thousands, as in the delay of the landmark ISIS-2 trial.4 More speculatively: if the UK COVID-19 human challenge trials (HCTs) that eventually took place in March 2021 had instead taken place in the summer of 2020, they might have meaningfully accelerated vaccine approval, saving countless lives. HCTs are the deliberate infection of low-risk volunteers with a pathogen, and have produced numerous important insights in microbiology since the 18th century. Experts from March 2020 onward made a clear case that HCTs could save thousands of lives by accelerating vaccine availability by a few months. Unfortunately, IRBs have looked askance at HCTs for conditions that lack effective treatment. 

In the US, a COVID-19 challenge protocol was rejected, even though 35 members of Congress signed an open letter asking HHS and the NIH to explicitly consider human challenge trials, and there was broad public support for challenge trials. In the UK, an HCT was eventually successfully conducted in February 2021, more than a year after COVID-19 emerged, and the delay was due in large part to the ethics review process.5

A hidden cost is the biomedical research that is never carried out as a result of IRB deterrence. Sometimes this may be riskier but higher-reward research; in other cases, IRBs may deter less well-funded researchers who don’t have the time to deal with multiple rounds of IRB approval. Early-career scientists with a tenure clock ticking away in the background also suffer disproportionately from IRB delays, as do students. 

Worst of all, the IRB system shows no signs of recognizing its limits. IRBs have even tried to regulate high-school science fair projects. Consent forms grow ever more byzantine, a far cry from the index card consent of the mumps vaccine trials, as Dr. Paul Offit documents in Vaccinated:

Parents interested in participating in the study received a three-by-five-inch card stating, “I allow my child to get a mumps vaccine.” At the bottom of the card was a line for the parents’ signatures. Unlike the practice today, the consent card didn’t contain an explanation of the disease, a description of the vaccine, a list of vaccine components, a discussion of previous studies, the need for blood tests, or a statement of possible risks and benefits. Parents were also given Robert Weibel’s work and home telephone numbers. If they had any questions about the vaccine or if they were worried that the vaccine was causing a problem, they could call him at any time, day or night. Weibel, in turn, would drive to their homes and examine their children.

Quality improvement research in hospitals is coming increasingly under IRB scrutiny as well, imperiling the ability of healthcare systems to quickly learn and iterate from internal data. 

The IRB system has occasionally retreated in the face of sustained criticism, as when Ithiel de Sola Pool argued several decades ago in The New York Times that they suppress academic freedom. They largely left social scientists alone in the 1980s as a result. And in 2011, more than a dozen federal agencies initiated a revision of the official Common Rule guidance to address the many grievances scientists had voiced over the years. But overall, these moments of reform have been a disappointment. The only substantive reforms that emerged out of the 8-year Common Rule revision process were the following: a determination that multi-site trials should be centralized in single IRBs; that researchers did not have to ask IRBs if research was exempt; and an explicit recognition that oral history was exempt from IRB review. Per personal communication with involved parties, these revisions were a resounding disappointment to the busy researchers who spent precious time submitting public comments to little effect. 

Solutions

Given the clear costs of our current IRB system and the failures of self-regulation, what is to be done? One tempting solution is to get rid of the IRB system entirely. Multiple eminent legal scholars have argued along these lines. In The Censor’s Hand, Carl Schneider argues that given previous failures of IRB reform, only wholesale abandonment of it can work. Columbia law professor Philip Hamburger has argued that IRBs are a serious threat to free speech since they’re effectively a licensing system for speech and thus a target for First Amendment offensive litigation.

Judicial lawfare on the IRB system is a tempting option and should be pursued in parallel, but my sense is that non-government forces that demand IRB oversight will serve as a backstop in that scenario. Scientific journals, for instance, usually demand that authors seek IRB approval. Universities might still demand IRB oversight as a condition of employment. Perhaps public university IRBs may end up substantially curtailed through such a strategy, but that is uncertain. So something like an IRB system will probably remain in place as long as large institutions are risk-averse.

Instead, I will lay out a series of incremental IRB reforms, all of which could be implemented through direct and unambiguous Congressional legislation, since federal bureaucrats have previously demonstrated a willingness to ignore presidential and public demands. Current federal IRB regulations were developed by federal agencies, who were delegated this authority by Congress. Congress can exercise this original authority to more precisely target regulation. 

Some Reforms

The following are reforms that maintain IRBs in some form but fix their biggest problems. Ideally all of these reforms would be implemented, but each would be useful on its own. 

As professor Ryan Briggs has proposed, researchers who make small changes in a study protocol should be able to self-certify that their changes meet a de minimis standard, avoiding another round of IRB review and revision. Some IRBs only meet every few weeks or months, so an extra round of IRB review for small changes in a protocol means substantial delay, slowing scientific progress. If researchers abused this privilege and tried to smuggle in substantive changes to their protocol, they would forfeit this ability.

A similarly narrow reform is implementing an electronic checklist that would allow researchers to self-determine if their research was low-risk and did not require IRB review. A University of Chicago professor, Omri Ben-Shahar, has developed exactly such a tool, and OHRP has no objection, but clear federal guidance would assuage the worries of risk-averse university administrators, who often still require IRBs to approve exempted studies. If universities continued to delay the use of such a tool, Congress could make receipt of government funds conditional on developing and allowing such a tool. 

Holly Fernandez-Lynch, a Professor at the University of Pennsylvania, argues that greater IRB transparency is sorely needed. In their current incarnation, IRB decisions are opaque to researchers and even other IRBs. In contrast to our legal system, which is built on precedent, every IRB decision is effectively made de-novo, which results in high heterogeneity between IRBs. Transparency would help every member of the research ecosystem: researchers would better understand which protocols would need modification, and IRBs would learn from each other’s best practices. Confidentiality would be reserved for commercially sensitive protocol sections and kept to a minimum.

Any attempt at IRB reform should also focus on what is likely the largest recent cost imposed by IRBs—the lack of timely human challenge trials (HCTs) for COVID-19. To prevent such delays in the future, Congress ought to lay out specific timelines for the ethics review process of HCTs in pandemic situations and grant substantial legal protection to involved investigators and institutions. The FDA already has the legal authority to approve vaccines based on challenge data – the missing link is a clear signal to IRBs that obstruction and delay are not acceptable in pandemic situations. While Congress can directly write this exemption into law, an alternative for more cautious legislators is granting an independent commission, like the original National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research itself, the authority and mandate to develop fast and ethical guidelines for HCTs in pandemic situations.

If Congress has greater appetite for IRB reform, a more sweeping approach would be removing social science from IRB jurisdiction altogether. Historian Zachary Schrag, who worked intensely to lobby federal agencies on the Common Rule revisions from 2009-2017, proposes this in his book, Ethical Imperialism. As he documents, the Belmont Report, and subsequent regulatory developments, were not designed with social science in mind. Congress could fix this historical oversight by changing the wording of HHS regulations. This would free IRBs to focus on truly high-risk research instead of wasting time on low-risk social science research. Since social science more often touches on political questions, this would also extricate government-mandated oversight boards (IRBs) from the delicate position of regulating politically charged research.

After many decades of stifling scientific progress, it is time for targeted but substantive IRB reform. Such an effort could recruit a bipartisan and pro-progress coalition. Leading center-left journalists Ezra Klein and Matthew Yglesias have both criticized IRB failures, while influential libertarians like Alex Tabarrok and Tyler Cowen are natural allies in streamlining unnecessary government red tape. Common-sense IRB reform is desperately needed and likely to succeed.

Willy Chertman is a graduate of the University of Miami Miller School of Medicine and PGY-1 internal medicine physician at Holy Cross Health Hospital Fort Lauderdale. He writes about medical innovation, regulation, and the history of science. Subscribe to his Substack and follow him on Twitter @Willyintheworld.

Subscribe now

Read the other prize-winning essays from the CSPI Essay Contest:

• “Gathering Steam: Unlocking Geothermal Potential in the United States” by Andrew Kenneson

• “Mo’ Money Mo’ Problems” by Maxwell Tabarrok

• “Drone Airspace: A New Global Asset Class” by Brent Skorup

• “The University-Government Complex” by William L. Krayer

I’m therefore pleased to announce that CSPI is going full Substack. This means that all of our blog posts, reports, links, podcasts, and other communications are going to be released through the Substack interface at www.cspicenter.com from now on.

Under the old system, when we had new content to share, you would first learn about it through Substack via e-mail or the app. Then, you would click through to the CSPI website. If you wanted to listen to a podcast afterwards, you might click on the “podcast” tab on the website, then go to Audioboom, and finally click on the Apple or Spotify logo to get it in the relevant app. If you decided you liked what you heard, you could click the “donate” tab on the website, which gave you the option of sending money through Patreon or PayPal.

Or maybe, if not yet a subscriber to the newsletter, you might have come across a CSPI report on Twitter. You’d then find yourself wanting to keep up with what we are doing, but for you to join our mailing list we needed to hope that you clicked on the “subscribe” tab, which would take you to the Substack.

Now, everything is integrated into one place. Next time we release a new blog post or report, you will again get an e-mail or alert through the app. But this time, you can read it right on your phone or computer without going anywhere else. If you’re a new reader and discover CSPI through social media or a news article, when you click on our page you will be prompted to sign up for future e-mails or alerts right then and there. If you want to listen to a podcast or make a donation, you can also do those things on the same website.

As I wrote in April,

Throughout much of my adult life, I’ve subscribed to three newspapers: The New York Times, The Washington Post, and The Wall Street Journal. A decade ago I would wait until I got each newspaper in my inbox every morning and read what I thought looked interesting. Then they all got apps, and those became a much more convenient way to keep up with the news. The NYT was the first to develop a really good one, and I found myself reading more of that paper and less of the other two. Until recently the WP app was particularly bad. Every time I clicked on a story, it was basically a crapshoot as to whether I was still even logged in. In the last couple of months, the WP unveiled a brand new app that is much easier to use, and it is now competing with the NYT as my main source of news.

The secret to the success of Substack is that, like Netflix, it has perfected the frictionless experience. This is true for both consumers and producers of content. Some months ago, I was talking to an academic with a blog, and I told her she should get on Substack because I liked the fact that it was so easy to sign up for e-mails. She told me that I could just go to her WordPress site, scroll or direct my eyes to the right place, and subscribe to her blog too. What’s the big deal? Sounds like the same thing. I tried to get through to her that I’m a very busy guy who already finds it difficult to keep up with everything I want to read, and I’m sure other potential readers are in the same position, so five seconds versus one second to sign up for a blog is a big difference…

The case for Substack became even stronger with the release of its app just last month. It’s at least as good as those of the NYT and WP, and provides a much better experience than I got when I used to send all my Substacks to an e-mail folder and then scroll through it every now and then. I’ve never once been logged out of Substack against my will, whether on the app or through my browser, which is something that is extremely rare for any website. They even got rid of passwords! When I need to log in on a new device or browser, they simply send a link through e-mail. Yes, in theory using passwords should be no big deal now, as they are automatically saved in your browser. In theory. In practice, perhaps a quarter of the time when I try to log in with a password I think I’ve previously saved, something goes wrong.

As part of the move, we’ve brought along all of our past blogs and reports, along with our podcasts. The one part of the old website we haven’t been able to bring over yet in its entirety is Philippe’s blog, since its posts include a lot of fancy math that uses LaTeX, which Substack currently doesn’t support. We’ve been in discussions with Substack and they hope to solve this problem soon, at which point we’ll move all of Philippe’s previous writing here too. For now, we will release his future blog posts that don’t require LaTeX through Substack, along with all of our other content.

In case you’ve missed any of our previous reports, you can find them posted on the new CSPI site below.

1. The National Populist Illusion: Why Culture, Not Economics, Drives American Politics – George Hawley and Richard Hanania

2. Academic Freedom in Crisis: Punishment, Political Discrimination, and Self-Censorship – Eric Kaufmann

3. The Accuracy of Stereotypes: Data and Implications – Lee Jussim and Nate Honeycutt

4. Increasing Politicization and Homogeneity in Scientific Funding: An Analysis of NSF Grants, 1990-2020 – Leif Rasmussen

5. About Those Baby Brainwaves: Why “Policy Relevant” Social Science is Mostly a Fraud – Jordan Lasker

6. Born This Way? The Rise of LGBT as a Social and Political Identity – Eric Kaufmann

As a 501(c)(3), CSPI is only able to continue our work through the generous support of our readers.

We are doing something very unique in providing fearless critiques of elite dogma in an empirically rigorous way that can reach broad swaths of the media. See our 2021 recap on what we were able to accomplish last year.

Unlike other institutions, we don’t apologize for findings that sound harsh or are politically incorrect and therefore upsetting to most elites. Nor do we only speak to the other side of the political spectrum, bending or shading the truth in order to make our writing conform to a different agenda. If that appeals to you, please consider a donation.

FIRST PLACE ($5,000):

Gathering Steam: Unlocking Geothermal Potential in the United States, by Andrew Kenneson

Andrew works for a public housing authority in Kodiak, Alaska. Before that, he was a reporter at local newspapers in Kodiak and in Monroe, Georgia. His email is akenneson21@gmail.com.

SECOND PLACE ($2,500):

Mo’ Money Mo’ Problems: A Proposal For Science Funding Reform, by Maxwell Tabarrok

Maxwell is an Econ and Math student at the University of Virginia. He blogs at maximumprogress.substack.com. Follow him on Twitter @MTabarrok.

THIRD PLACE ($1,000):

Drone Airspace: A New Global Asset Class, by Brent Skorup

Brent is a senior research fellow at George Mason University's Mercatus Center and a visiting faculty fellow at the Nebraska Governance and Technology Center at the Nebraska College of Law. Follow him on Twitter @bskorup.

HONORABLE MENTIONS ($500):

The University-Government (U-G) Complex, by William L. Krayer

William is a 92 year-old semi-retired intellectual property lawyer and past president of the Pittsburgh Intellectual Property Law Association.

It’s Time to Review the Institutional Review Boards, by Willy Chertman

Willy is a graduate of the University of Miami Miller School of Medicine and PGY-1 internal medicine physician at Holy Cross Health Hospital Fort Lauderdale. He writes about medical innovation, regulation, and the history of science at willyreads.substack.com. Follow him on Twitter @Willyintheworld.

Congratulations to the winners. We will be publishing their essays over the next weeks and months.

Summary

• A recent study claimed small cash transfers to the parents of newborns improved their babies’ brain activity. The study was lauded in the media and by D.C. policymakers who argued its results supported redistributive policies, most notably the child tax credit.

• Closer inspection of the baby brainwaves study reveals its claims to be wildly overstated and its methodology to be suspect, as is common for policy relevant social science.

• Authors Troller-Renfree et al. committed numerous bad research practices, including:

  • Deviating from their analysis plan, and justifying it by referencing studies that did not support and even contradicted their results.

  • Highlighting results obtained through typically unimportant methodological decisions that weren’t preregistered.

  • Ignoring that larger and more prolonged interventions typically generate smaller effects than they found, meaning their results were likely due to chance or error.

• Looking beyond the study in question, the theoretical and empirical basis it claims to build upon is largely a house of sand. The evidence that is purported to show a link between brain waves and cognitive outcomes is extremely weak, and most interventions seeking to improve cognitive ability in children have small to nil effects.

• Despite its inconclusiveness, the study was portrayed as relevant to child tax credit policy, vigorously promoted in media outlets like Vox and The New York Times, and championed by think tanks and policymakers.

• These issues are not unique to the baby brainwaves study. Social scientists frequently engage in questionable research practices and exaggerate the strength and implications of their findings. Policymakers capitalize on low-quality social science research to justify their own agendas. This is particularly true when it comes to research that claims to improve cognitive and behavioral outcomes.

• Thus, we ought to be skeptical of social scientists’ ability to reliably inform public policy, and of policymakers’ ability to evaluate social-scientific research objectively, particularly when it is “policy relevant.”

Introduction

On January 24th, 2022, The New York Times published a piece that went out as a news alert titled “Cash Aid to Poor Mothers Increases Brain Activity in Babies, Study Finds.”2 The article discussed Troller-Renfree et al. (2022), a study published in the Proceedings of the National Academy of Science (PNAS) that purported to show a monthly subsidy of $333 yielded considerable improvements in children’s brainwave activity.3 Vox also covered the story, opining that “we can be reasonably confident the cash [parents received] is a primary cause of these changes in babies’ brains. And we can be reasonably confident it will be a causative factor in whatever future outcomes the… researchers find.”4 They weren’t alone: think tanks, medical news aggregators, and other mainstream outlets like NBC and Forbes all praised the study and the alleged psychological benefits of brainwave improvements.5

Laudatory coverage was accompanied by claims that the study had special relevance to expanding child tax credits. The study authors even put out a pro-child tax credit press release on their website: “This study’s findings on infant brain activity… really speak to how anti-poverty policies – including the types of expanded child tax credits being debated in the U.S. – can and should be viewed as investments in children.”6

High praise and lofty implications aside, a closer examination of the study reveals its results to be dubious and its methods severely flawed. While the authors’ public statements portrayed the study as strong, reliable, and policy relevant, none of these claims hold up to scrutiny. The study and its portrayal stand as excellent examples of what can go wrong when political desire supersedes scientific reasoning, and why we ought to be skeptical of social scientists’ ability to reliably inform public policy with their research. A deeper dive into the problems with this study and the literatures it purports to build upon are therefore warranted.

Several academics and public intellectuals pointed out flaws in Troller-Renfree et al.’s (2022) study shortly after it was released. Psychologist Stuart Ritchie noted the article’s potentially-dubious peer review status, the disconnect between observations made by the study’s authors and outcomes that matter, the potential for fade-out effects, deviations from preregistered methodology, and the nonsignificance of the reported effects of cash transfers on any of the study’s main outcomes.7 Statistician Andrew Gelman found that the significance of results was not robust and that the graphs produced by the authors could be replicated even if the children in the sample were randomized into artificial treatment and control groups.8 Finally, psychiatrist Scott Alexander offered further commentary on the article to the effect that the results seemed unlikely for various reasons, alongside a summary of what other people had said.9

In this article, I show that Troller-Renfree et al.’s results were even less robust than critical commentators said they were. The study’s results not only reveal sloppy methodological choices, but indicate that the authors took extra steps to portray their findings as more policy relevant than was warranted. And even if their findings were wholly accurate, which is highly unlikely, their policy suggestions would not follow from their results. While this essay assumes only a passing familiarity with the study in question, I have also written a full-length report that contains a longer and more technical discussion of the study and expands upon some of the work from Ritchie, Gelman, and Alexander.10

Problems With the Literature Linking EEGs to Psychological Outcomes

For the results of Troller-Renfree et al.’s study to be important, changes in electroencephalography (EEG) power11 would need to be causally linked to changes in its psychological correlates, such as IQ or language skills. The study’s authors cited several pieces of research that supposedly linked EEG power to their desired, preregistered cognitive outcomes, and studies relating EEG power to socioeconomic status (SES). Cumulatively, Troller-Renfree et al. argued that these studies linked absolute power in mid-to-high frequency bands to linguistic, cognitive, and social-emotional development, while simultaneously arguing that low-frequency band power was linked to behavioral and learning issues.     

However, these studies suffered from many major problems: failing to deal with the issue of multiple comparisons, small sample sizes and low power, inconsistent results, confounding with genes and family environments, representativeness problems, various reporting errors, and nonsense models. The relevant descriptive statistics for their cited studies relating EEG power to cognition are provided in Table 1, and the studies relating it to SES are in Table 2. I cover the problems with these studies in greater depth in the full-length report, but here I give a short overview of some of the basic flaws in their literature:

Multiple Comparisons

When too many tests are run, the likelihood of getting a false-positive significant effect increases. This is the problem of multiple comparisons, and it is amenable to a graphical explanation. Figure 1 illustrates the relationship between the number of statistical tests and the probability that at least one of the results is significant if there is no true effect, based on a significance level of 0.05.

The typical study in Tables 1 or 2 below had well over ten tests, but most also did not correct for multiple comparisons, so the risk of false positives was high in the literature cited by Troller-Renfree et al.

Small Samples and Low Power

Small sample sizes are a serious problem in scientific research because studies that rely on them lack statistical power: the probability that a statistical test detects a real effect of a given size at some level of significance. If I have a sample size of 20 and I need to find a correlation between X and Y that has a p-value below 0.05, the lowest significant correlation would be Pearson’s r = 0.44. If I quintuple my sample size, the lowest significant correlation is 0.20. This does not mean that a small sample cannot yield small correlations, only that, when it does, they will not be significant.

The issue with small sample sizes is also open to graphical explanation. Figure 2 illustrates the relationship between sample sizes and the average sample correlation conditioned on reaching a 5% significance threshold (the mean significant correlation) in simulated data with different true underlying correlations. The mean sample sizes in Tables 1 and 2 were 89 and 67, respectively. If the true correlation is typical of the correlations observed in large, reliable studies in neuroscience (closer to 0.10), we can infer that the correlations in the studies Trolley-Renfree et al. cited were exaggerated by 2.6 to 3 times.12

There is some evidence in Tables 1 and 2 that suggests these effect sizes were exaggerated, because smaller studies had larger effects. Moreover, there was a significant negative correlation between the size of correlations and their precision,13 an indication that researchers were probably trying to find significant results and, as such, had to find and publish exaggerated effects because their samples were too small.14

Table 1. Study Descriptives for Cited Cognitive Ability-EEG Studies15

Table 2. Study Descriptives for Cited SES-EEG Studies16

Unrepresentative Samples

The studies cited by Troller-Renfree et al. had problematic and unusual sampling. Some of the studies featured samples of people with congenital heart defects,17 some of the samples had very high average IQs, in another 85% of the sample’s parents belonged to the highest socioeconomic strata and a third of the involved families had histories of language impairment, and so on. The samples were often decidedly unrepresentative of the general population, so it is difficult to generalize from them.

Problems With the Study Itself

Gaming Preregistration

Small studies lead to inconsistent and overstated effects. Combined with an editorial bias towards papers with statistically significant results, they encourage scouring datasets for significant relationships (commonly known as p-hacking). One way to limit the pernicious effects of searching for significance is for researchers to preregister the hypotheses they intend to check, forcing them to report specific outcomes they may have decided not to publish due to a lack of significance.

Troller-Renfree et al. preregistered that they were going to examine effects on theta, alpha, and gamma power. Respectively, these are brainwave frequency bands ranging from 4 – 8, 8 – 13, and >35 Hz. Curiously, their largest effect was in the beta band (13 – 35 Hz). They preregistered their intention to investigate only alpha, gamma, and theta because, when they formulated the study, the literature showed effects on those bands – not beta. However, “between 2018 and the present investigation,” they wrote, “evidence has emerged linking income to beta activity, including from the first and senior authors’ lab.”18 Two studies were cited to support that claim.

The first study they cited linking beta to income was by Brito et al. (2020). It was entirely cross-sectional and featured, at most, correlations in a study of 60 kids. It yielded no significant relationships between SES and beta or gamma power, either by region or in total, and it also showcased no relationship between SES and a child’s auditory or expressive communication abilities. The second study by Jensen et al. (2021) was the largest study among those cited, with a sample size of at most 187. If this study is taken seriously, it contradicts Troller-Renfree et al. because it found no relationships between SES and EEG power for their sample of 160 6-month-olds, and negative relationships between SES and both beta and gamma power among their 187 36-month-olds.

Troller-Renfree et al. found a positive effect of their intervention on both beta and gamma, despite their cited beta evidence being consistent with no effect or a negative one. If Troller-Renfree et al.’s reasoning was truly informed by these two studies, they should have been alarmed to find that two high-frequency bands, gamma and beta, within which power may have been negatively related to SES were increased by their experiment, indicating kids may have been harmed by the intervention.

Moreover, Troller-Renfree et al. did not preregister their choice of robust estimator or treatment effect size. They used regression to estimate the effect of treatment, and to avoid their estimates being affected by violations of any of the several assumptions involved in regression, they utilized robust estimation, a way of running their regressions while obviating issues with its assumptions. There are many types of robust estimators and different statistical software uses different default estimators. In Stata, the analysis program they used, the default is HC1 – a robust estimator that is common by virtue of its default status rather than its performance. More advanced robust estimators exist, and they ought to be used to deliver accurate results when, for example, samples are not very large, like theirs. Using HC5, a more modern alternative, I found that their significant results became wholly nonsignificant (i.e., p > 0.05 before correction).

The effect size of their treatment was computed by dividing their adjusted treatment effect by the standard deviation (SD) of their control group; a common method for computing standardized treatment effects. However, they could have also divided by the pooled SD, either weighted by each group’s sample size or not. That they did not use the pooled SD would not normally be an issue, but out of all the effect size computation methods they could have chosen, they picked the one that delivered them two significant results prior to multiple comparison correction.

Similar Magnitudes Don’t Matter

Troller-Renfree et al. wrote that, “[d]espite the limitations in statistical power, the pattern of impacts, which resulted from a rigorous random assignment study design, were consistent with hypotheses, were similar in magnitude to effects on cognitive outcomes from other scalable interventions, and were largely robust to various tests, leads us to conclude that these findings are important and unlikely to be spurious.” But they never explained why these similarities mattered. If several studies show that giving children iron improves growth by five centimeters (d = 0.25), I wouldn’t be able to use that finding to show that teaching children chess and finding that they had more theta wave activity (d = 0.25) was more plausible just because we can draw vague links between them and the effect sizes are the same. The studies have no necessary relationship with one another. They deal with different interventions and outcomes, so the effect sizes in each domain probably should differ. The mere fact that it’s possible to generate a likely chance finding about one does not vindicate its comparison with another.

Long-Term Treatment Effects and Parental Responsibility

Despite its weak evidentiary basis, effusive support for Troller-Renfree et al.’s article has been common. Representative Suzan DelBene (D-Wa.) was quoted by The New York Times saying it showed “investing in our children has incredible long-term benefits.”19 In the same venue, Duke economist Lisa Gennetian – one of the study’s co-authors – claimed the study showed parents could be trusted to spend money well. Neither piece of commentary finds any support in the study. The former is nonsensical because the study only covered a single year, not the long term, and the latter is simply not viable because, for one, the study did not examine how well money was spent, and our only way to assess this was to look at the money’s effect on children.

Moreover, because the authors of the study controlled for variables that indicated parental misbehavior – smoking and alcohol consumption during pregnancy, marital status, and maternal mental health – they removed the ability to draw inferences about how well parents used the money in the same way that controlling for the quality of the venue, service, preparation, and ingredients makes it difficult to accurately compare McDonald’s and a five-star restaurant. It would have been reasonable to adjust the data if there were no systematic differences in attrition, and randomization between the treatment and control groups was satisfactory, but their controls remove our ability to draw certain conclusions.

Most Interventions Have Small to Nil Effects

Troller-Renfree et al. exaggerated the sizes of the effects from other studies that they used to validate their own. The citation they provided for the similarity of their experimental effect with other interventions was Kraft (2019), who performed a large meta-analysis of educational interventions and found a meta-analytic effect size of 0.16 d.20 However, Kraft’s data was typical of meta-analyses in that it suffered from a bias towards studies with significant effects that were typically small. The weighted effect size was 0.04 d - one-fourth as large, and not significant. Lortie-Forgues and Inglis (2019) conducted a similar study, but theirs did not suffer from the same problems as Kraft because they analyzed studies funded by organizations that required the trials they supported to be published in a standardized fashion.21 The effect size they found was 0.06 d, and the median study in their analysis was consistent with anecdotal evidence for no effect; that is, the quality of the evidence for the median study should not have been regarded as substantial enough to support change in belief about intervention effectiveness.22

Other interventions have also had similarly minor effects. The 2010 Head Start Impact Study conducted by the Office of Planning, Research and Evaluation looked at effects elicited by the Head Start program for three- and four-year-old children.23 Using a p-value cutoff of 0.10, it found significant positive effects on eight of fourteen cognitive tests given in the year of the program for the three-year-old children, and this reduced to two of 14 by the next year, at age four. In kindergarten, there were 19 tests administered, with one significant positive effect, and one significant negative one, while, in the first grade, only one effect of twenty-two remained significant. Because this was not significantly affected during Head Start and its effect only became significant amongst a pile of nonsignificant ones, it was probably noise. For the four-year-old group, seven of 14 scores were significantly positively affected in the Head Start year, but effects disappeared in kindergarten, and one effect became significant again in first grade. Relatedly, Duncan and Magnuson (2013) found that the effect sizes associated with childcare programs declined over time.24 When I repurposed Duncan and Magnuson’s data, there was a negative relationship between a study’s precision and how large an effect it produced – publication bias!25

Studies of nutritional interventions have fared similarly. Dulal et al. (2018) ran a double-blind RCT in Nepal where groups of mothers were given prenatal multiple micronutrient supplementation in the treatment group, and iron and folic acid only in the control group.26 At 12 years of age, there were no effects on children’s cognitive ability. Behrens et al. (2020) reviewed whether vitamin B affected rates of cognitive decline and found no effects, despite well-defined mechanisms and plausible effects at the time of writing.27 Similarly, a large-scale follow-up of two double-blinded, placebo-controlled, cluster-randomized trials of vitamin A effects on prenatal and newborn children by Ali et al. (2017) yielded nonsignificant effects across the board.28

Even when the intervention is medical in nature, effects are often minute. Welch et al. (2018) reported the results of a systematic review of deworming effects on a variety of outcomes including cognitive ability, height, and weight.29 Despite parasitic worms often being debilitating and the mechanisms through which they should impede development being abundantly clear, there were no significant meta-analytic effects on weight, height, or cognitive ability. Welch et al. (2018) compared their results to earlier systematic reviews by Taylor-Robinson et al. (2015) and Welch et al. (2016), which, altogether, found one marginally significant meta-analytic effect on weight and none for height or cognitive ability.30

Analyses of cash transfers specifically have not yielded large effects either. Zimmerman et al. (2021) evaluated the effects of cash transfers on psychological distress and depression and found evidence consistent with no effect.31 There may have been effects on variables like an individual’s outlook, hope, and feelings of power in their sexual relationships, but these would have nonetheless been modest, imprecise, and insufficiently replicated. Manley et al. (2020) examined cash transfer effects on more plausible outcomes – height, weight, dietary diversity, the consumption of animal-based foods, etc.32 Among published studies, smaller studies had larger effects, indicating a small study bias, but there was a significant effect (p-value between 0.05 and 0.01) on stunting. Among unpublished studies, there was more concentration of effects around zero, and the aggregate effect on growth stunting was nonsignificant. With some evidence for publication bias, the strongest interpretation of that meta-analysis is a marginal effect on meaningful growth parameters. The full-length report contains additional details on several other relevant studies.

Perhaps if the cash transfers were massively scaled up, they might have an effect. Certain studies do seem to look like extremely extensive and large-scaled interventions. For example, the Moving to Opportunity program that relocated people from low- to high-quality neighborhoods had an extraordinary economic value, but it failed to elicit an effect on measured mathematical and reading skills.33 Perhaps that was because family inside the home has a much greater effect than the location of the home. Adoption puts people into new homes and families that are generally much wealthier and better educated than their birth families or the general population, amounting to a natural experiment in giving people comprehensively high SES. The effects from good adoption studies generally span between nil (Ericsson et al., 2017) and just over the effect size Troller-Renfree et al. observed (Kendler et al., 2015).34

Some people object to adoption studies on the grounds that we cannot properly control for preadoption circumstances and their persistent effects on children. But when Korean adoptees in Sweden were examined, there was no relationship between age at adoption and subsequent cognitive ability.35 The reason for this appears to be that Korea would not allow people to select which baby they wanted, so in the absence of parental selection, the relationship between age at adoption and subsequent performance breaks down.36 With the size of adoption effects noted, we can plot how they compare to the cross-sectional association between parental SES and cognitive performance. Figure 3 does this and shows that despite adoption affecting how well people score (their performance), the effect is not strong enough to generate the same relationship between SES and performance that we see in the general population, where SES is tied not only to people’s environments, but also to their genes.37

The issue of genetic confounding is extremely important. Cross-sectional studies like the ones discussed here are generally not informative for Troller-Renfree et al.’s purposes because associations between variables like SES and specific brainwave patterns may occur due to a common cause or correlated causes. In the case of comparisons between members of different families, the issue may be genetic confounding – where genes explain the relationships among different outcomes, like EEG power and family income. The relationship between intelligence and brain white and gray matter volumes is accounted for by shared genes.38 Similarly, the relationship between socioeconomic status and intelligence has been found to have a substantial genetic component, and the link between the two is virtually severed when genetics are accounted for.39 Even EEG power is heritable, with most relationships among EEG power at different frequencies attributable to shared genes.40

As a result of substantial genetic influence and other potential forms of confounding, how are we to generalize from experimental effects on EEG parameters to cross-sectional samples or vice versa? Troller-Renfree et al. were at least somewhat aware of these facts, as evidenced by their citation of Wax (2017), who argued that “the so-called neuroscience of deprivation has no unique practical payoff… Because this research does not, and generally cannot, distinguish between innate versus environmental causes of brain characteristics, it cannot predict whether neurological and behavioral deficits can be addressed by reducing social deprivation.”41

Policy Conclusions Were Unwarranted

Troller-Renfree et al. have attempted to sell their results as relevant to the ongoing debate over child tax credits. Their press release for the study said as much, and mainstream sources have used their results to justify child tax credits on the grounds that they will make kids’ brains work better.42 Since the strong interpretation of their results is unwarranted, so is the conclusion that the child tax credits are justified by brain improvements. Insofar as the results were basically uncertain, it was wrong to frame them as policy relevant.

But child tax credits do present an interesting opportunity for study, albeit outside of the context of Troller-Renfree et al.’s flawed work. If their conclusions were totally correct and we could generalize the largest of their effects on EEG power to some psychological trait like intelligence, we should be able to pick that up in children’s achievement now. Children whose parents received child tax credits can be identified, and we should see a major boost in their achievement down the line. Those who believe interventions timed earlier in life have larger effects have an appropriate test in the form of credits to families with kids of varying ages, and people who believe effects should persist should expect the ability distribution of those whose families received cash when they were younger to be raised. If the case for child tax credits based on cognitive improvement is as strong as Troller-Renfree et al. and others suggested, the effects will be extremely noticeable. To get an idea of how big this could be, if the IQ of the population increased by 0.26 SDs, we would have almost three times as many people with IQs of 160 or greater, and almost half as many with IQs of 70 or less.43

After their study was published, Troller-Renfree et al.’s work received immediate pushback. Many who were quick to give the study plaudits recalibrated their judgements upon learning about its flaws. The UBI Center removed their posts about the study, the Niskanen Center put up a disclaimer, and even Vox updated its coverage to feature critical commentary.44 Unfortunately, Vox also published a dubious response from the study’s lead author, Kimberly Noble.45

She confronted criticisms with a curious argument, arguing that the results were robust because the authors observed predicted region-specific relationships. This was obviously untrue, as the prior literature does not and could not adequately suggest region-specific associations unless she failed to cite it in the article. Moreover, the associations did not survive when I corrected for multiple comparisons (i.e., p became greater than 0.05 universally), which were done incorrectly for this section of the paper. As discussed, work claiming to find region-specific associations requires a lot of power that studies in this literature lack. Noting that you can perform a bunch of tests and recapitulate your initial results does not mean they were supported, it means you think transforming your data and finding the same things you did prior to transformation bolsters your initial conclusions. Anyone could do this and claim any finding is robust, regardless of topic. All it signals is a desire for the study to be considered important rather than its quality.

Conclusion

Troller-Renfree et al. conducted an intervention where poor families were given $333/month; income subsidies equal to around 20% of their prior incomes. Their results were nonsignificant impacts on infants’ EEG parameters. They inferred that if there were effects, they might have been important because other literature linked some of the ostensibly affected EEG parameters to important cognitive outcomes and did so with magnitudes apparently comparable to educational interventions.

Troller-Renfree et al. needed two things to be true for their study to be important. First, they needed a treatment effect on EEG power. Second, they needed specific changes in EEG power to causally impact important psychological traits like cognitive ability, depression, ADHD, etc. The evidence for a treatment effect was absent from their study and the evidence in favor of any link, much less a causal one, between specific bands’ EEG power and desirable psychological outcomes was tenuous at best. The groundwork needed for their results to be treated as if they were meaningful or to even treat their inferences as more than a passing flight of fancy was not provided and may not exist. For results based on a chain of reasoning about previous findings to be taken seriously requires that chain be strong, and this one was not.

The authors had the opportunity to test if manipulating an aspect of SES impacted cognitive outcomes, and they did so via proxy. Per their theory, SES impacts the brain, which impacts cognition, but the links between SES and EEG parameters – much less EEG and psychological ones – were so tenuous as to render the theory not only unevidenced, but wholly useless. Given that their paper was systematically tilted towards a positive interpretation of essentially null results, it was, in essence, an explanation of their theory, rather than a test of it.

Using weak science to advocate for policy is a frequent occurrence. Most social science is weak, and journalists and activists are often looking for evidence that confirms what they want to believe. Troller-Renfree et al. provided a case study in many of the most typical mistakes made by people who want to support a cause without doing the legwork. They asked us to not only accept their methods, but their interpretations and theories relying on a chain of strong relationships that have yet to be shown to exist. Those who believe this study has any policy relevance should start placing bets that there will be a massive uptick in rates of genius and plummeting rates of mental disability in the U.S. because of recent child tax credits. There won’t be.

The public arena is at least somewhat self-correcting, in that the findings in Troller-Renfree et al. were quickly scoured in the popular press. The bigger problem, however, is that if it had not gotten a write up in the New York Times accompanied by a news alert, and if the study’s topic and author’s framing had not been so palpably absurd, the paper may have never been carefully checked and the results may have turned into conventional wisdom. Bad science is the norm; correcting it is not.

Cases like this ought to make us reconsider the role social science plays in our public policy debates. Political bias and confirmation bias are heuristics that plague us all, and we have no reason to think that social scientists or policymakers are immune. Flashy results that support a popular policy are usually untrustworthy, and large effects are usually exaggerated, p-hacked, or due to chance. The reality is that most social interventions and policies have a negligible impact when it comes to improving cognitive ability or behavior. Until researchers and the educated public come to grips with this fact, we should be skeptical of policymakers’ ability to evaluate research objectively and social scientists’ ability to reliably inform public policy with their work.

Jordan Lasker is a PhD student at Texas Tech University. 

The presentation provides an accessible overview of Philippe’s work detailing the failure of epidemiologists to accurately model transmission, the ineffectiveness of non-pharmaceutical interventions (NIPs) like masks and lockdowns, and how including network community structure as a relevant variable could improve pandemic modeling.

CSPI Essay Contest

On a different note, those of you who are new to CSPI should know that we’re currently sponsoring an essay contest, with the theme of “Policy Reform for Progress.” We’re looking for 1000-2000 word submissions that propose a plan for a reform that can facilitate or remove a barrier to the development or application of an important new technology, such as self-driving cars, commercial space travel, or anti-aging treatments.

We’ve received several submissions so far, but there’s still plenty of time left before the March 31st deadline for you to submit your own essay. Whether you’re a student, academic, or industry professional, this is a great opportunity to get people thinking about an important issue in a new light. Feel free to reach out if you have any questions.

1st prize is $5000, 2nd prize is $2500, and 3rd prize is $1000. A to-be-determined number of essays will get $500 each. Submissions will be judged by CSPI’s fellows and members of the progress studies community, and prize-winning essays will be published on our website and brought to the attention of policymakers. 

To learn more, check out our post where we outline the rules of the contest:

Political and institutional change are rarely the result of mass persuasion – they usually take place because a small group of highly motivated individuals who care a lot about ideas have an outsized impact on the public discourse and convince elites to see things in a new way. Thanks to CSPI’s research and analysis, public intellectuals and policymakers are thinking differently about political intolerance in academia, non-pharmaceutical interventions (NPIs) for stopping COVID-19, the relationship between wokeness and civil rights law, and a number of other important issues. People are hungry for concrete solutions to deal with failing institutions and stagnant bureaucracies, and we’re filling a unique role in the intellectual ecosystem.

If you’ve appreciated the work we’ve done this year and want to see our scholars succeed in the year to come, there are a few ways you can support us:

1. Rate and review the CSPI podcast on Apple, Spotify, or wherever else you listen.

2. Subscribe to the CSPI Substack for $10/month, $100/year, or, for the truly generous, $500/year.

3. Donate a more substantial amount to CSPI by sending an inquiry to contact@cspicenter.org, and we’ll be in touch.

If you value our eclectic mix of institutional analysis, social theory, “expert” debunking, and progress studies, please consider making a financial contribution. There’s no other think tank or group of researchers doing quite what we’re doing, and your money goes directly towards supporting our scholars and their projects.

Below is a summary of the work we’ve done in the past year.

Academic Freedom

Right-wing and centrist scholars have long complained about anti-conservative bias in academia and its downstream effects on free speech and free inquiry. Eric Kaufmann’s landmark report, “Academic Freedom in Crisis,” was the first comprehensive survey of political intolerance in academia, finding ample evidence of discrimination against right-leaning and gender-critical scholars in hiring, promotion and other areas.

His report also shed light on the beliefs of academics, demonstrating that when it comes to issues like decolonizing the curriculum or firing controversial scholars, many are torn between their commitments to free speech and social justice. Nonetheless, there is no “silent majority” of academics who prioritize free speech above all else.

The report was widely discussed throughout the press, including in the New York Times, Wall Street Journal, City Journal, and Bloomberg. University of Austin president Panos Kanelos cited it as one of his reasons for founding a new university dedicated to protecting free speech. Kaufmann’s recommendations are currently informing the UK Government’s Higher Education Bill, which will extend free speech protections for students and academics.

COVID-19 and the War on Science

During the coronavirus pandemic, we’ve seen doctors, epidemiologists, and public health officials gain unprecedented levels of power over political and economic decisions. In an age in which we’re repeatedly told to “trust the science” and “listen to the experts,” it’s never been more important to criticize bad science and question the legitimacy of scientific authority.

Philippe Lemoine has shown that scientists studying COVID consistently get even the most basic things wrong. His first article for CSPI, “The Case against Lockdowns,” demonstrated that lockdowns and other NPIs have in most places not had notable effects on COVID transmission and likely fail any reasonable cost-benefit analysis.

His subsequent pieces have identified other scientific failures, such as epidemiologists’ inability to accurately model the pandemic, their attribution of declining case numbers to non-pharmaceutical interventions instead of voluntary behavior or the impact of networks, and widespread alarmism in the face of new variants like Delta and Omicron. He has written on these topics for The Wall Street Journal and Le Figaro, and his work is regularly discussed in outlets like New York Magazine, and on blogs like Astral Codex Ten, EconLib, and Andrew Gelman’s Statistical Modeling, Causal Inference, and Social Science.

Richard Hanania also wrote on public health officials’ inability to think clearly about COVID, and the problem with “experts” more broadly. In “Are COVID Restrictions the New TSA?” he lamented the rise of “hygiene theater” and government officials’ inability to engage in cost-benefit analysis, while in “The Weirdness of Government Variation in COVID-19 Responses,” he asked why people have been relatively incurious and indifferent about regional or country-level differences in COVID policy. His article “Tetlock and the Taliban,” which he adapted into a New York Times op-ed, argued that most “expertise” is fake – the product of over-credentialization and appeals to authority – and that real knowledge and insight are often incompatible with intellectual diversity or narrow specialization.

Woke Institutions and Ideology

In the last decade, liberals have shifted far to the left on issues of race, gender, and sexuality. Ideas once considered radical – like defunding the police, getting rid of high-school gifted programs, and giving puberty blockers to children – are embraced by more people than ever before in the name of social justice.

One focus of CSPI’s researchers has been evaluating the origins of woke ideas and institutions, and proposing solutions to combat woke bureaucracy, which increasingly manages and controls more aspects of our personal and professional lives. Richard Hanania has been a leading figure in proposing such solutions, and his ideas are changing how conservatives think about the relationship between government policy and cultural change. In “Why is Everything Liberal?” he argued that liberals control institutions because they care more about politics than conservatives, sparking a lively debate among political commentators including Ross Douthat, Ezra Klein, Scott Alexander, and Robby Soave.

After responding to comments and criticisms, he followed up with “Woke Institutions is Just Civil Rights Law,” in which he argued that wokeness is largely the product of Civil Rights-era government policies and the HR bureaucracies that sprung up to enforce them. This piece prompted responses from Tyler Cowen, along with articles in City Journal from Charles Fain Lehman and Gabriel Rossman, culminating in a CSPI podcast episode where the two authors joined Richard to discuss the relationship between woke institutions, civil rights law, and corporate culture.

Zach Goldberg, CSPI’s resident “Wokeness Studies scholar,” kept his finger on the pulse of public opinion, tracking changes in the beliefs and attitudes of Americans on issues of race, identity, and political ideology. He recently defended his PhD dissertation, “Explaining Shifts in White Racial Liberalism: The Role of Collective Moral Emotions and Media Effects,” which he plans on turning into a book. His work chronicling “The Great Awokening” and changes in racial sentiment were cited this year in The Economist and the New York Times.

Martha Bradley-Dorsey started a project to gather basic budgetary information from 200 public universities to see how much money was being spent on diversity, equity, and inclusion (DEI) initiatives and administration. Unfortunately, this information was largely undocumented or unavailable, meaning legislators and the public have no way of evaluating the financial costs of DEI spending in universities. The fact that she was unable to gather what should be basic and publicly available spending data demonstrates the barriers to evaluating the ballooning costs of college bureaucracy, and that state governments should demand greater budgetary transparency from their public universities.

Social Science and Public Affairs

CSPI was founded to fund research on unexplored topics in the social sciences – high-quality scholarship of public interest that is unlikely to be supported in traditional academic environments. In our first year, we’ve produced several studies of political behavior and electoral politics that highlight the psychological factors underlying support for political parties, candidates, or causes.  

Eric Kaufmann conducted a survey of Black Americans’ racial identity and party identification, finding the subjective importance of Black identity to be a strong predictor of Democratic partisanship. These results were discussed in his New York Times op-ed “How Stable is the Democratic Coalition?,” in which he argued that the Democratic party may lose minority voters as they become less attached to their racial or ethnic identities.

George Hawley and Richard Hanania coauthored “The National Populist Illusion: Why Culture, Not Economics, Drives American Politics.” The report brought together a variety of evidence showing that anti-immigration attitudes and a disdain for political correctness were good predictors of voting for Trump in 2016, while economic factors like income were not.

They adapted this report for a National Review article, and Hanania was invited onto the TV show Rising and The Realignment podcast to discuss the myth of a working-class Republican party.

Jack Thompson and Sierra Davis, CSPI’s first grant recipients, researched why people support QAnon, and whether certain messages could decrease belief in the conspiracy. They found that associating QAnon with racism or anti-Semitism decreased support for it, while learning that Congressional representatives had expressed support for QAnon in the past increased support among Republicans.

Lee Jussim and Nathan Honeycutt summarized decades of research on stereotype accuracy. Their analysis shows that most stereotypes that have been studied are approximately correct at the group level, and that efforts to reduce stereotypes in education, government, and business as a means of achieving equality are generally misguided in light of this inconvenient fact.

Jonah Davids argued that most social science research is false, useless, or obvious. He suggested that moderates and conservatives’ focus on making academia more tolerant has blinded them to how underwhelming it is, and that young people who are passionate about social science would be better off doing private sector or independent research.

Philippe Lemoine wrote about Éric Zemmour, a right-wing populist intellectual running to be the next President of France on the grounds that he can stop the “great replacement.” The piece provided an overview of Zemmour’s life, ideas, and electoral prospects, and detailed his strengths and weaknesses as a candidate and likelihood of winning the presidency.

Progress and Policy

As part of CSPI’s new mission, we’ve begun funding and supporting research into knowledge production and modern governance. We believe that by realigning the organizational incentives of dysfunctional institutions, we can change them for the better – increasing their capacity to foster social and scientific progress rather than contribute to societal decay and stagnation.

Scientists are, or at least used to be, thought of as freethinkers working in pursuit of truth and innovation, but institutional incentives can steer their research towards what is professionally or politically expedient, rather than what is genuinely worthy of study. Leif Rasmussen’s analysis of successful National Science Foundation grant abstracts demonstrates how scientific research funding has become increasingly politicized. He found that the frequency of documents containing woke terms has increased consistently over the last three decades. In 2020, no fewer than 30% of successful grant abstracts contain one of the following words: “equity,” “diversity,” “inclusion,” “gender,” “marginalize,” “underrepresented,” or “disparity.”

His research also shows that successful grants have been getting more similar over time, which suggests a decline in the diversity of ideas funded. His findings were featured in National Review, the Washington Examiner, and Marginal Revolution.

While politics is often contentious and divisive, we believe that the right reforms can have an outsized effect on technological development and, ultimately, economic growth. That’s why we recently announced our first essay contest, “Policy Reform for Progress.” We’re seeking submissions that propose a plan for a reform that can facilitate or remove a barrier to the development or application of an important new technology, like self-driving cars, commercial space travel, or anti-aging treatments. Anyone can enter, and winning essays will receive cash prizes, be promoted on our website, and brought to the attention of policymakers.

***********************************************************************

CSPI is only possible because you read our research, listen to our podcast, and care about the ideas we’re putting forward and the questions we’re asking. Make sure you’re subscribed to our Substack, Twitter, Podcast, and YouTube to stay up to date on developments in 2022.

Happy New Year to everyone, and thank you for your support.

CSPI is interested in the social and political determinants of scientific and technological progress. While politics is often contentious, we believe that certain reforms, although unlikely to excite passion among a wide swath of the public, can have an outsized effect on technological development and, ultimately, economic growth.

In that spirit, we are pleased to announce an essay contest under the theme of “policy reform for progress.” We’re seeking submissions that propose a plan for a reform that can facilitate or remove a barrier to the development or application of an important new technology, such as self-driving cars, commercial space travel, or anti-aging treatments.

CSPI fellows and members of the progress studies community will judge the contest, and the winners will be announced 2-4 weeks after the deadline. 1st prize is $5000, 2nd prize is $2500, and 3rd prize is $1000. A to-be-determined number of essays will get $500 each, and there will also be honorable mentions. Prize-winning essays will be published on our blog and website, promoted, and brought to the attention of policymakers. 

Contest Rules:

1. Each essay should focus on a regulatory reform that would accelerate progress in an important technological or scientific area in the American context.

2. You must cite the specific regulatory law or policy you want to create or change, the benefits to be gained, and say something about what would be required (i.e., new statute, agency-based decision, executive order, etc.). The last part may require a bit of legal research, yet that shouldn’t be too hard for anyone with an interest in technology and regulation. We’re looking for realistic proposals, something like a new agency with the budget of the Pentagon and total control over the economy would be unlikely to win. Proposals will be judged based on some combination of their likely effects on scientific and technological progress and their political feasibility. The goal is to provide practical guidance to policymakers and regulators.

3. We’re interested in proposals for regulatory reform, not necessarily deregulation. This means proposals that call for more government intervention in an area and those that call for less are both acceptable.

4. There is no specific word count, but somewhere around 1,000-2,000 words should be appropriate.

5. If you have more than one good idea, you can submit multiple proposals, within reason.

6. Co-authored pieces are fine, but you will have to split any winnings. Collaborations between technology experts and legal experts might be particularly fruitful.

7. The contest is open to all, but students and other young people are particularly encouraged to apply.

8. DEADLINE: All essays must be submitted to contact@cspicenter.org by March 31, 2022. They should be submitted in a Word document, with the email title ESSAY CONTEST. You should get a confirmation that your entry was received. If you don't, let us know.

9. To stay current on any updates on the contest, subscribe to this newsletter.

If you’re wondering whether a topic is suitable or have any other questions, send us an email at contact@cspicenter.org. 

Good luck!

UPDATE: See the winners here.

Over the last four years of my life, my number one priority was getting into graduate school. There’s nothing I enjoy doing more than learning, reading, and researching, and graduate school seemed like the best place to do that. As a psychology undergraduate, I worked in multiple research labs, took online courses in programming and statistics, and read a lot of extra books and papers to supplement what I was learning in class. In my fourth year, I applied to a few graduate programs and got into my #1 choice; a 2-year master’s in political communication research at the University of Amsterdam.

As soon as I started school in September, I felt something was off. Talking to the other students, I realized all of us shared a common story: we were smart kids who did well in our undergrad, and graduate school just seemed like the “natural next step.” None of us could explain why we were in this particular program, or give an account of how it would advance our careers. Some, including me, hinted at the possibility of a PhD, but this was just deferring the question of “why are you here,” not answering it.

I was expecting the “school” portion of graduate school to be exciting and interesting, but I quickly became frustrated. Roughly half of the assigned papers were pre-replication crisis, so I didn’t know whether I should believe the results or not. The other half were post-replication crisis, and they were boring; just table after table of trivial correlations wedged between a lengthy literature review and an over-generalizing discussion section. I seriously doubted that studying these papers would get me closer to the truth on important matters rather than further away from it.

Within the first month, I managed to secure a research assistantship with a professor. But in the same private meeting where I was offered the position, the professor confided in me, saying that like me, they were “also very skeptical” of a lot of the research in the field, including some pieces they taught in their class. Now, one way to take this would be to think to myself, “wow, this professor is being really honest with me about the limitations of the research; that’s great.” Instead I thought to myself, “jeez, in class the professors are teaching these papers but in private they’re skeptical of them; that’s not good.” More conversations with other students and faculty confirmed this for me. In class these theories and findings were treated seriously. In private they were ridiculed.

During this period, I got along very well with the other students and faculty, and I never felt uncomfortable expressing my opinions in class. The people in my program expressed a wide range of political views and I’d say the median viewpoint in any given classroom was old-school liberalism. But the fact that I wasn’t distracted by concerns over “radicals on campus” or “leftwing bias” only made me more cognizant of how much I actually disliked the graduate school experience and how little faith I had in the value of the research.

So two months into graduate school, I dropped out. It was an easy decision.

Having spent some time reflecting on my experience in graduate school and within academia more generally, I’ve come up with what I believe were my three main reasons for leaving. The first is that I didn’t believe the academic literature I was studying was true, useful, or insightful. The second is that most of the students and faculty had beliefs about people and society that I felt didn’t square with the empirical evidence. The third is that I was much more interested in the social science research happening outside of academia. In the remainder of this post, I’ll discuss these reasons further in-depth, treating them not just as personal reasons for leaving academia but as good reasons for anyone to leave, or never to begin graduate school. The reasons I discuss aren’t unique to my program, department, or sub-discipline. They pervade social science academia, with some fields being worse than others.1 That’s why I’m comfortable generalizing from my experience studying communications, psychology, and political science to the social sciences more broadly.

We’ve all read pieces that criticize academia for being too woke or too bureaucratic, and while I touch upon those issues, my main criticism is just that it’s incredibly underwhelming.

1. Most of What You Study in Social Science Academia is False, Useless, or Obvious

I learned about the replication crisis a quarter of the way through my undergrad. I had the uneasy feeling that most of what I was learning was probably fake; that much of the social-scientific literature was one big house of cards that should have fallen years ago. But my focus on the replication crisis blinded me to a larger truth: that most demonstrably true social science research findings are useless or obvious.

Useless findings sound interesting, but for all practical purposes they don’t matter. You can tell a nice story about the findings, and they might even be statistically significant, but the effects are so tiny as to render them inapplicable to any real-world prediction or application. This is the fate of many social-scientific studies, which tell a nice story about the difference between groups – Democrats and Republicans, single and married, control and treatment – but gloss over how tiny the differences are. A classic example is an influential political psychology paper called “The Secret Lives of Liberals and Conservatives.”2 The authors found several liberal-conservative differences in personality, behavior, and even what items people had in their bedrooms and offices. But as one psychologist critical of the paper pointed out, “the ‘secret lives’ title is apt” given how small the differences are and how little of their variance can actually be attributed to political ideology.3

Obvious findings are those you probably could have known about without empirically researching them. They’re more useful than useless findings (obviously), but you can’t tell a good story about them because the story would be boring. For example, people who are more interested in politics are more likely to know a lot about politics and to vote, or people who post about protests on social media are more likely to attend them.4 I think social science is heading in this direction, and while the studies are getting more scientifically precise, the results are getting less interesting and surprising as a consequence.  

There are social science findings that are true, useful, and counterintuitive, but they are rare, probably less than 1% of published research. Most of the findings that appear to fall under this category are ‘too good to be true,’ and are eventually revealed to be p-hacks, flukes, or fabrications, though they still get cited a lot!5 More often than not, the true, useful, and counterintuitive findings are null results: you think something mattered, and it turns out not to matter at all. Unfortunately, null results rarely get the attention they deserve due to publication bias.

Many professors and graduate students are aware of these issues but cope with them by saying, “we’re getting better now that we have open science research practices.” What they don’t realize, or prefer not to think about, is that as social science methodology has improved the findings have become more useless and obvious. Most counterintuitive results fail to replicate or are disproven, and effect sizes shrink with bigger samples and more control variables. What’s left is often so banal or self-evident that it’s not clear why it needed studying in the first place. I’m not suggesting we go back to how we used to do social science, where bad statistics and small samples artificially inflated effect sizes. But I am suggesting we grapple with the fact that social-scientific advancement has revealed most social science research to be of little to no value.

2. Most People Studying Social Science Have the Wrong Priors

Social science students and academics frequently hold a set of views that other scientists have refuted. They often think that gender is a social construct, or that parenting matters more than genetics in determining social and psychological outcomes. Many believe they can fix complex social issues like poverty, racial disparities, or political polarization by reminding people of their biases or ‘nudging’ them towards pro-social behaviors.6

I would say that many who study social science overweight the influence of social factors and behavioral interventions and underweight the impact of biological factors, random variance, and culture. Rather than adjust their priors, they tend to double-down on their belief that tiny effects matter or that obvious results are surprising.

If they were to adjust their priors, expecting most social factors and interventions to have little impact if any, two things would happen. First, a literature chock-full of tiny effects would be taken as evidence that a phenomenon isn’t worth studying in-depth. Second, consolatory statements like “humans are complicated” or retreats into philosophy of science would be seen for what they are: attempts to cope with the disparity between social reality and social reality as perceived by social scientists.

There is value in studying and reporting null results and small effects, but only if we’re honest about what they mean. The value comes from slashing false lay-beliefs about social phenomena (i.e., “advertisements are highly effective”) rather than constructing a story about the importance of those phenomena when the data argue the opposite. However, most people who choose to study social science don’t go into it expecting small effects and null results. They go into it thinking the effects will be big and the results will be socially significant. Were they not under this impression, who would knowingly pay money to study a subject?

3. The Most Innovative and Impactful Social Research is Happening Outside of Academia

Good social research often requires large, high-quality datasets. The biggest social/behavioral datasets are owned by companies like Facebook, Nielsen, and Palantir, and governments that collect a lot of data on their citizens, such as China. Unlike academia, the businesses and institutions that collect this data have massive budgets and often collect data on real behavior instead of approximating it in a laboratory setting or survey. They also operate with fewer ethical constraints than in academia, where even the simplest, most inoffensive survey must be cleared by an ethics committee. This can take anywhere from several days to several weeks, unlike in business research or media where you can put out a survey instantly. For example, a presidential approval poll would require an ethics review in academia, but not if done for a newspaper.

I'm not suggesting the problems described above, like small effects or non-replicable results, are absent from non-academic research. These issues exist in most research environments, public or private. But in a non-academic setting, you’ll have the opportunity to work on projects that matter; that help a business identify a market and sell a product or help a government understand its citizens and predict their behavior. The feeling that you are doing work that “matters” is incredibly important to the kinds of people who get involved in social science, and venturing outside of academia to work on projects with tangible impacts is one way of recapturing that feeling. Projects also get done a lot faster outside of academia, which helps you quickly determine whether the research you’re conducting has value or not.

But let’s say you don’t care about the nitty-gritty empirical data and are more interested in social science theory. It’s reasonable to suspect that academia might be a better place to study theory than a private company or government, but is it where the best social theory is emerging?

I’d argue that the best modern social theory comes from three non-academic sources. The first is blogs and newsletters, where top journalists, political actors, and social theorists are sharing their research and insights for free or a small monthly fee. The second is the tech world, which makes sense considering our thoughts, feelings, and actions are increasingly expressed online or through technology. The third is social media platforms like Twitter and Reddit, where novel social and political theory is frequently proposed, discussed, and dissected.

I don’t deny that interesting theoretical work comes out of academia, but academia holds no monopoly over the study of people and society. And if your goal is to propose new social theory, you’re better off being entrepreneurial with your ideas instead of getting bogged down in academia’s incentive structure, which discourages innovation and favors incrementalism.

Final Thoughts

Many people on the right and heterodox left are concerned about the lack of conservative voices on campus, particularly in the social sciences and humanities. There are far fewer right-leaning faculty, and right-leaning students are less likely to enroll in an undergraduate program or pursue post-graduate education than their left-wing classmates.7

These are troubling issues that deserve to be addressed, but I think moderates and conservatives’ desire to make academia a more politically tolerant place may have blinded them to how unremarkable contemporary academia actually is. Even if 50% of social science faculty were right-wing and moderate or conservative students felt perfectly comfortable expressing their views and values, I don’t think it would justify their spending more time in academia, splitting hairs and boiling the ocean.

There’s never been a better time to study people and society empirically. Books and articles are easily accessible, publicly available datasets are abundant, and conducting survey research is cheap with services like MTurk or Prolific. You can learn statistics, programming, and survey design skills through online courses or private tutoring, which cost a fraction of graduate school tuition fees. Or you can join a company or government with access to big datasets and go crazy with multiple regression.

Life is too short to spend reading outdated articles and writing pointless papers, and people and society are too interesting to be studied in such a myopic manner. So if you’re thinking about graduate school or are already enrolled but not enjoying yourself, do something else instead.

Jonah Davids is the director of communications at CSPI.

QAnon is a conspiracy theory in which a cabal of Satan-worshipping pedophiles is running a global child sex-trafficking ring and was plotting against Donald Trump throughout his presidency. Since 2018, an increasing number of Americans have become aware of QAnon, primarily through social media sites such as Facebook and online forums such as Reddit.

Understanding why QAnoners believe what they believe is by no means an abstract or niche question. The dissemination and acceptance of QAnon-related misinformation has had a number of real-world implications since the emergence of the conspiracy in 2018. For instance, the spread of misinformation about child sex trafficking led Polaris, an anti-human trafficking organization, to warn that its hotlines were being overwhelmed by false reports, thus preventing individuals from providing valid information.

In 2019, the FBI also published a report expressing concern over the potential for QAnon beliefs to motivate individuals to commit political violence – the first time the agency had rated a fringe conspiracy theory. These concerns were realized on January 6, 2021, when many QAnon believers were arrested for taking part in the storming of the U.S. Capitol building.

By identifying the types of messages that might lead to a weakening in support for the conspiracy, a variety of actors – for instance, non-profit organizations, government agencies, and social media platforms – should be better placed to develop strategies to combat misinformation.

In our new paper, we conducted an experiment to learn what types of messages might change QAnon beliefs, relying on a representative sample of 1,405 Americans. In testing what types of messages might increase support for QAnon, we exposed survey respondents to some information about QAnon support in Congress. We identified two Representatives – Marjorie Taylor Greene (GA-14) and Lauren Boebert (CO-3) – to use in our experiment. When respondents learned that these Representatives had expressed support for QAnon in the past, we found that they became more likely to support the movement relative to those who did not receive this information. However, this effect was largely driven by Republican respondents, who exhibited significantly higher levels of support for QAnon than Democrats who received the same information.

In testing for what types of messages might decrease support for QAnon, we also exposed survey respondents to some information about racist and anti-Semitic posts on Voat.co, a Reddit-esque news aggregator that provided a platform to many QAnoners. When respondents became aware of these posts, we found that such individuals expressed less support for QAnon. Racism and anti-Semitism are taboo belief systems, and by connecting them to QAnon, it may be possible to reduce support for the conspiracy theory.

We also tested whether learning about the origins of QAnon on the fringe online message board 4chan, or the many incorrect predictions made by QAnon influencers, led to a decrease in support for the conspiracy. We found that exposure to this information mostly had no effect either way.

Beyond these various messages, we also found that a number of individual-level factors shape support for QAnon. Specifically, QAnon supporters knew less about politics, and were more likely to be Republican, politically conservative, younger, non-Hispanic and Catholic.

Our results indicate that, if non-profit organizations, government agencies, and social media companies wish to better combat misinformation and dispel conspiracy theories, then an effective strategy might be to connect them to racist and anti-Semitic views. Political endorsements also seem to matter, although when they were combined with disconfirming information in our experiment, the effect went away.

Even if the percentage of Americans who support QAnon remains in the low single figures, the events of January 6 indicate that any changes in support might be critically important for reducing the number of individuals who ultimately engage in political violence.

Jack Thompson is a Postdoctoral Research Fellow at the University of Exeter. His research interests include misinformation attitudes and voter behavior.

Sierra Davis is a PhD student in Political Science at Stanford University and a graduate fellow at the Stanford Center for American Democracy. Her research interests include political beliefs and partisanship, gender in politics, elections and voting behavior, and ideology and public opinion.

For decades, universities have worked to be more inclusive. Recently, they have rebranded these efforts under the general heading of Diversity, Equity, and Inclusion (DEI) and given those in charge of such initiatives more resources and power. Universities nationwide have added DEI offices without replacing other departments with similar goals, and have promoted such efforts as central to the university mission. To their supporters, DEI initiatives have led the charge toward more inclusion. To their opponents, they are a waste of money at best, and at worst, a force behind the growing intolerance towards dissenting views gripping universities and society more generally.

The figure above shows the increase in bureaucracy in the University of California system between 2000 and 2015 alone.

Regardless of where one stands in this debate, both sides can benefit from more information about these efforts. Just how much taxpayer money is being spent on DEI, and what are the offices doing? In order to find out, I began a research project for CSPI to gather basic budgetary information across a large number of universities. Unfortunately, it failed miserably. 

Cutting the project several ways, I first cast a wide net to find budget information for 200 publicly funded universities from all 50 states’ budget officials. While nearly all responded to my “public-information law” requests, I learned that many state fiscal officials don’t maintain any detailed university budget information. They frequently keep only high-level university budget data. Considering that public universities receive about $171 billion in government funding annually, it was frustrating to find out that information about how money was spent was not easily available.

In response, I decided to undertake a less ambitious program. Using a much more modest public university sample, I directly asked seven individual universities’ public information agencies for their budgets on programs and offices regarding every DEI-associated term I could think of (“diversity, equity, inclusion, Title IX, women, African Americans, Latinos/Latinx/Hispanics, Native or Indigenous Americans, LGBT or any derivative thereof, Asian Americans, or migrants or immigrants”). This, too, proved unsuccessful. While two universities provided me with a detailed budget showing at least some of our requested information, an official from another institution stated there was “no search mechanism available that would allow us to identify the offices included in your keyword search.” The official then asked us to read through their “A to Z” office contact list (with 88 listings under the letter “A” alone) to select the relevant offices. She would then “work with our budget officers” to obtain the requested information. Cost: $30 or $75 per hour, depending on whether the specific request involves “database extraction.” Of the final four, one has promised a response by August 3, another has promised a response by some unspecified date, and two have completely ignored the request. 

This brief foray into DEI budget searching revealed that, even if we had sufficient resources and time to make the relevant requests, it would be a massive undertaking and no matter what happens we would not be able to obtain comparable information across universities and states, nor any budgetary information at all from many universities. Back to Square One.

To make decisions about the value of DEI initiatives, legislators need to know what is going on in public universities, but as of right now, it does not appear that they can in most places.

In my decades-long career working for two state legislatures, I repeatedly witnessed bureaucracies operating in deeply stacked hierarchies and labyrinthine organizational charts, their activities opaque even to the trained eye. Universities are among the worst offenders. Be assured that – apart from any “greater good” objective – bureaucracy protects itself from anything it views as a threat. Public information laws alone cannot get behind this wall.

Universities have in recent decades been overrun with bureaucracy, much of it of dubious utility. I undertook a project hoping to at least get an accounting of how much money public institutions have been spending on DEI efforts. Despite laws meant to facilitate information being made available to the public, legislators and citizens continue to be in the dark about what exactly universities are doing with their resources.

Given the highly bureaucratic nature of the university, it is probably unrealistic to hope that this will ever change. Legislators have many things to worry about, while university staff can work full time to protect their prerogatives and interests. If it is impossible to find out exactly what the DEI bureaucracy in public universities is doing, the best path forward may be for state governments to make their own decisions about the value of more support staff and make sure that the aggregate budget reflects their choices.

Martha Bradley-Dorsey is a distinguished doctoral fellow in the Department of Education Reform at the University of Arkansas and interested in helping find greater educational opportunities for disadvantaged students and researching the effects of bureaucracies on those opportunities.

With all this success, some have noted a disconnect between our stated mission and the work we’ve been doing. While CSPI was originally focused on the academy and improving the state of scientific research, the interests of our fellows have led us in a more policy-oriented direction, although while always maintaining the highest empirical standards. Consequently, our first half year has taught us that there is a large market out there for rigorous research that speaks to the most pressing issues of the day.

One of the best pieces of advice I received when starting this think tank was that events will always ensure that an institution never goes in the exact direction its founders intended. CSPI has been no exception, and having undertaken a shift in practice already, we have decided to make it official. CSPI has updated our mission statement and our list of topics of interest. We are moving away from more theoretical work to research that is more practical and policy relevant, and away from a focus on individual psychology towards an interest in the bureaucracies, structures, and systems that translate knowledge into political and social outcomes. At the same time, we are maintaining our commitment to non-partisanship and the highest standards of empirical rigor.

CSPI was founded in the midst of the COVID-19 pandemic. My evolution in how I have thought about the crisis has paralleled my thinking about CSPI and what it should be doing. We had begun with the assumption that academia was broken. What became clear, however, was that our institutions were failing in more fundamental ways. Epidemiologists began by telling us COVID-19 was nothing to worry about and that masks did not work. They failed to understand and communicate the simple fact that this was a respiratory disease, not one that spread through contact with surfaces. And while, as Philippe Lemoine shows, it may have been rational to support lockdowns when our knowledge was limited, when it became clear that they didn’t have much of an effect, most restrictions should have been lifted given their massive costs. A recent poll of epidemiologists showed that 81% of them wanted to keep Americans wearing masks indoors for at least another year, despite the invention of a vaccine that brings the risk of hospitalization or death to zero, and the fact that we are approaching the point where everyone who wants a vaccine is able to get one for free. The next public health crisis may cause us to defer to the same experts again, a truly frightening thought given their extreme irrationality.

These failures cannot be explained by epidemiology being too hard of a science. We know this because, throughout the pandemic, non-epidemiologists like Alex Tabarrok and Zeynep Tufekci have usually been ahead of the field, which has all but admitted this by eventually moving to their position weeks or months after they originally made their arguments. It is not simply that the prominent epidemiologists are wrong, but that they refuse to do anything resembling cost-benefit analysis.

The massive failure of epidemiology would perhaps not be enough to change the mission of CSPI if it were an isolated case. Yet I have become convinced that its failures are generalizable. There are recurring themes in the inability of American society to deal with important challenges: political bias driving scientific conclusions; the practice of “safetyism” in which trade-offs are ignored; and expertise claiming authority on the basis of credentialism and often useless domain-specific knowledge, rather than an ability to engage in statistical reasoning and cost-benefit analysis.

Other areas of life show an increase of expertise coinciding with problems staying the same or getting worse. The United States spends more on education than any society in human history yet has mediocre test scores. Despite technological improvements, the cost of infrastructure and rates of violent crime are both higher than they were in the 1950s. Nuclear power is clearly a good option for helping solve climate change, yet the industry has been regulated to death. Other developed countries have similar problems to a greater or lesser degree. The constant theme is that the relationship between expertise, the production of knowledge, and how knowledge gets communicated and translated into policy is broken.

The Roots of Progress website seeks to understand at a fundamental level what makes society function in ways that are conducive to human flourishing, and that project and others like it have helped inspire our shift. In 1911, while reviewing a book on an extremely narrow topic, W. Warde Fowler wrote “We are getting to know more and more about less and less.” No one can doubt that, over a century later, the problem is much worse. At CSPI, we believe that there is an intimate relationship between the problems of our intellectual life and the stagnation or decline in many areas important to societal well-being.

Instead of simply focusing on underexplored topics in the social sciences, CSPI now seeks to fund and support research on systems of knowledge production and communication, and how they relate to social and political outcomes.

The new mission of CSPI is both more ambitious and more difficult. We believe studying the most important questions is worth the extra effort; to focus exclusively on the problems of academia, much of it irrelevant to the outside world, would be to help replicate the intellectual trends we are concerned with.

If you are interested in contributing to our project or learning more, please don't hesitate to email us at contact@cspicenter.org. We look forward to continuing our journey with you.